The Structure of the Cultural Syndrome 'Individualism-Collectivism' in Ukraine

Abstract

Three approaches were used to study the structure of the cultural syndrome
"individualism-collectivism" in Ukraine: the "spatial" structure (factor structure, age,
gender, regional characteristics, structure at the in-group level, connection with
individual religiosity) was studied using the Singelis et al. (1995) scale; the temporal
structure (dynamics of individualism-collectivism components over time, starting from 1900) was studied using content analysis and Schwartz’s value scale.

Full text

TARAS SHEVCHENKO NATIONAL UNIVERSITY OF KYIV
INSTITUTE OF CONTINUING EDUCATION
MASTER'S THESIS
THE STRUCTURE
OF THE CULTURAL SYNDROME
'INDIVIDUALISM-COLLECTIVISM' IN UKRAINE
Student: Third-year student
of specialty 7.03010201 “Psychology”
Part-time study form
Borysenko Leonid Hryhorovych
Academic supervisor:
Ph.D. in Psychology, Associate Professor
Kravchuk
Svitlana
Leontiivna
The work has been approved for defense before the Examination Committee
by the decision of the Academic and Methodological Commission
dated «____»___________________2017, protocol No__
Director of the Institute Doctor of Economics, Professor Rozhko O.D.
Kyiv – 2017

2
TABLE OF CONTENTS
INTRODUCTION 5
CHAPTER 1. THEORETICAL BASIS FOR THE STUDY OF
INDIVIDUALISM-COLLECTIVISM 9
1.1. Diversity of Approaches to Defining Culture 9
1.2. Major Approaches to Cross-Cultural Comparisons
1.3. Development of Ethnometric Research
1.4. Individualism-Collectivism as a Fundamental Cultural Dimension
1.5. Ukrainian Culture: Individualism or Collectivism?
13
17
19
21
1.6. Ethnometric Studies in Ukraine 22
1.7. The Structure of Individualism-Collectivism
1.8. Temporal Dynamics of Individualism-Collectivism
25
27
CHAPTER 2. METHODOLOGICAL JUSTIFICATION AND PROCEDURE
FOR EMPIRICAL RESEARCH 30
2.1. Methods and Stages of Studying the "Spatial" Characteristics of
Individualism-Collectivism
2.1.1. Selection of the Scale
2.1.2. Ukrainian Adaptation of the Singelis et al. (1995) Scale
2.1.3. Processing of Survey Results
30
30
31
35
2.2. Methods and Stages of Studying the Temporal Characteristics of
Individualism-Collectivism
2.2.1. Justification and Specifics of Applying the Content Analysis
Method
2.2.2. Work with the Google Books Ngram Database
2.2.3. Processing of Content Analysis Data
2.2.4. Work with the European Social Survey Database
36
36
38
39
42

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CHAPTER 3. ANALYSIS OF THE RESULTS OF EMPIRICAL RESEARCH 44
3.1. The "Spatial" Structure of Individualism-Collectivism in Ukraine
3.1.1. Factor Structure
3.1.2. Age, Gender, and Regional Characteristics
3.1.3. The Structure of Collectivism at the Level of In-Groups
44
44
51
57
3.2. The Temporal Structure of Individualism-Collectivism in Ukraine
3.2.1. Dynamics of Changes in Individualism-Collectivism During the
20th Century
3.2.2. Dynamics of Сhanges in Individualism-Collectivism in the 21st
Сentury
60
60
77
CONCLUSIONS 81
REFERENCES 84
APPENDICES 97

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LIST OF ABBREVIATIONS
VI - Vertical Individualism
VC - Vertical Collectivism
HI - Horizontal Individualism
HC - Horizontal Collectivism
EFA - Exploratory Factor Analysis
ESS - European Social Survey
I-C - Individualism-Collectivism
CFA - Confirmatory Factor Analysis

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INTRODUCTION
Relevance of the study. After a prolonged phase of the emergence of
cross-cultural psychology, where attempts to distinguish cultural differences were mostly
qualitative, the 1970s marked the advent of ethnometry — a quantitative measurement
of cultural components. The founder of ethnometry, G. Hofstede, provided data on the
measurement of "cultural values" in over 70 countries. Since then, the number of
countries covered by such studies has steadily increased. Among the various cultural
values (or "cultural syndromes," as termed by H. Triandis) identified through
ethnometric approaches, the "individualism-collectivism" syndrome occupies a central
place. This syndrome reflects the extent to which personal goals are prioritized over
group goals and is often referred to as the primary cultural dimension.
Ethnometric studies in Ukraine remain sporadic, and their results are often
contradictory. Despite the persistent myth of Ukrainian individualism, ethnometric
approaches reveal, at best, a slight predominance of individualism over collectivism.
Attempts to study the factorial structure and in-group level characteristics of this
dimension have not been undertaken in Ukraine. The same applies to studies of gender,
age differences, and the relationship of individualism-collectivism with religiosity, as
well as the temporal structure (dynamics) of its components.
Exploring this construct is of great interest. Such a study will not only clarify
Ukraine’s value orientations on the "mental map" of the world but will also shed light on
potential regional mental differences, especially between the East and West of Ukraine.
Additionally, an important issue is the transformation of value orientations during
societal transitions caused by historical events.
Research Object: the cultural syndrome "individualism-collectivism."
Research Subject: the "spatial" and temporal components of the cultural
syndrome "individualism-collectivism" in Ukraine.

6
Purpose of the study: To identify and analyze the characteristics of the "spatial"
(factorial structure, age, gender, regional differences, in-group structure, relationship
with personal religiosity) and temporal (dynamics of components over time, starting
from 1900) structure of the cultural syndrome "individualism-collectivism" in Ukraine.
Hypotheses of the study: 1) Individualism and collectivism are two independent
constructs; 2) The factorial structure of this cultural syndrome in Ukraine includes four
factors; 3) Ukrainians predominantly exhibit individualism over collectivism; 4) Women
exhibit higher collectivism and lower individualism scores compared to men; 5)
Regional differences exist: Western Ukraine demonstrates higher individualism, while
Eastern Ukraine shows higher collectivism; 6) Age negatively correlates with
individualism and positively correlates with collectivism; 7) Religiousness negatively
correlates with individualism and positively correlates with collectivism; 8) Stronger
in-group ties (immediate family, relatives, friends, colleagues, neighbors) positively
correlate with collectivist orientation; 9) During the 20th and early 21st centuries,
individualistic orientation in Ukraine has shown a tendency to grow.
Research Objectives: 1) To identify the main theoretical approaches to
interpreting the cultural syndrome "individualism-collectivism" and the methodological
approaches to its measurement; 2) To develop a Ukrainian-language scale for measuring
individualism-collectivism based on the Singelis et al. (1995) scale and investigate its
validity and reliability; 3) To study the factorial structure of individualism-collectivism
in Ukraine; 4) To examine age, gender, and regional differences in
individualism-collectivism in Ukraine; 5) To explore the relationship between
individualism-collectivism and personal religiosity as well as orientation toward specific
in-groups; 6) To analyze the temporal dynamics of individualism-collectivism in
Ukraine in the 20th century using content analysis; 7) To analyze the temporal dynamics
of individualism-collectivism in Ukraine in the 20th century using change point analysis;
8) To study the temporal dynamics of individualism-collectivism in Ukraine in the 21st
century by analyzing data from the European Social Survey, which included Schwartz’s

7
value measurement methodology.
Research methods: 1) Theoretical methods: analysis and synthesis of scientific
literature on cross-cultural research in general and the cultural syndrome
"individualism-collectivism" in particular; 2) Empirical methods: a psychodiagnostic
survey using the adapted Ukrainian version of the Singelis et al. scale (1995), content
analysis; 3) Statistical data processing methods: descriptive statistics, comparison of
means, correlation analysis, regression analysis, factor analysis, time series analysis, and
change point analysis; 4) Interpretative (structural) and organizational (comparative)
methods: comparison, identification of key characteristics of the obtained results, and
analysis of literary sources.
Scientific Novelty: All parts and stages of this empirical study are novel for
Ukrainian science. The study of temporal dynamics in pronoun usage is currently the
most extensive study of this type (114 words, spanning a 100-year period). The analysis
of change points in time series represents one of the first attempts to apply this type of
statistical analysis to the study of linguistic data dynamics.
Significance of the Results: Theoretical significance lies in systematizing
knowledge in cross-cultural studies in general and in quantitatively measuring the
cultural syndrome "individualism-collectivism" specifically, filling gaps in ethnometric
research in Ukraine, and broadening the understanding of the structure and temporal
dynamics of this cultural syndrome, including its dependence on factors such as age,
gender, and personal religiosity. Practical applications of the results include their use in
psychological and pedagogical work, business and cultural contacts, and international
communication.
Reliability and Validity: Ensured by statistically significant sample size (604
individuals) from various regions of Ukraine, a large number of books used for content
analysis (490.855 unique titles comprising over 55 billion words), a significant sample
of respondents surveyed using Schwartz’s scale in the European Social Survey (9.987
individuals). The combination of quantitative and qualitative analyses, along with

8
intensive use of mathematical statistics, further supports the reliability of the results.
Key Findings for Defense: 1) The factorial structure of
individualism-collectivism in Ukraine includes four factors; 2) During the 20th and early
21st centuries, an increase in individualistic orientation is observed in Ukraine; 3)
Modern Ukraine exhibits a predominance of individualistic over collectivistic
orientation; 4) Women, compared to men, demonstrate a predominance of collectivistic
orientation; 5) Age, strength of in-group ties, and personal religiosity positively correlate
with collectivistic orientation.
Thesis Approval: The main findings of the study were presented at the II
International Scientific Conference "Modern Psychology: Theory and Practice"
(Ivano-Frankivsk, May 6-7, 2016), III International Scientific Conference "Topical
Issues of Modern Psychology" (Dnipro, October 7-8, 2016), and IV International
Scientific Conference "The Relevance of Psychology in Modern Society" (Uzhhorod,
June 16-17, 2017).
Thesis Structure: The thesis consists of an introduction, three chapters, a list of
references (126 titles, of which 95 are in foreign languages), and appendices. The total
volume of the thesis is 105 pages, including 90 pages of the main text. The work
contains 16 tables and 7 figures.

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CHAPTER 1
THEORETICAL BASIS FOR THE STUDY OF
INDIVIDUALISM-COLLECTIVISM
1.1. Diversity of Approaches to Defining Culture
The concept of culture is one of the key ideas in the human sciences. Culture
encompasses a variety of phenomena, or so-called cultural universals, transmitted from
generation to generation through social learning. Cultural universals include language,
art, religion, technology, production means, social institutions, and more. Traditionally, a
distinction is made between spiritual and material culture; however, this division is
merely a "scientific abstraction" [6], as any material cultural artifact exists as an idea in
human consciousness before its creation.
Various definitions of culture aim to simultaneously capture both the universality
and diversity of the concept. Traditionally, definitions of culture reflect an "evolution of
ideas," showcasing the different meanings attributed to the concept throughout periods
and epochs.
It is well known that the term "culture" originates from the Latin verb "colere,"
meaning cultivation of land. Initially, this term was used exclusively in ancient Roman
agricultural texts. This practical definition of culture remains to this day (e.g.,
"agriculture", "aquaculture"). However, it quickly began to be used metaphorically.
Cicero, for instance, used expressions like "culture of the soul" and "culture of the spirit"
("cultura animae"), implying that the soul becomes "cultivated" when a person engages
in philosophy and the arts [66].
In the Middle Ages, the concept of culture was practically not used. Only in the
17th century, the German historian and philosopher S. Pufendorf essentially

10
rediscovered Cicero's metaphor and used this concept for the first time in its modern
interpretation. According to his definition, culture (German Kultur) is any product of
human activity as a member of human society. Pufendorf contrasted the "social" person
with the uneducated and uncultured "natural" person [6; 66].
This concept was further developed by the German philosopher J.C. Adelung, who,
in 1782, published a book titled "An attempt at a history of the culture of the human
race". German classical philosophers such as Kant and Hegel primarily relied on French
thinkers, using the term "civilization" synonymously with culture. Hegel, in particular,
equated civilization with the final stage of the dialectical evolution of spirit.
In French, the term 'civilization' was used instead of the German term Kultur, yet
it largely corresponded to the modern understanding of culture. For example, J.-J.
Rousseau actively contrasted civilization (culture) with nature, comparing civilized and
uncivilized peoples. According to him, the latter lived in harmony with nature and were
therefore happier; he cited the example of Native Americans before the European
conquest of their land.
The approaches of French Enlightenment thinkers later gave rise to numerous
ideas about the interconnectedness of the concepts of culture and civilization. For
instance, it is not uncommon nowadays to refer to culture as a higher stage of
civilization’s development or to regard civilization as the most complex and advanced
stage of cultural development. As noted by Kroeber and Kluckhohn [66], these concepts
in English are “almost synonymous”.
N. Danilevsky was likely the first to introduce the concept of culture into the
Russian language in the mid-19th century (from German, with its original, nearly
modern interpretation). In his book Russia and Europe, he developed the concept of
local cultures [5].
Danilevsky's work attracted the attention of the German philosopher O. Spengler,
who, unlike his predecessors, developed an original concept of the contrast between
culture and civilization. According to Spengler, civilization is a stage in the development

11
of culture characterized by a lack of creativity, productivity, and a stagnation and
crystallization of humanity. Civilization represents the final stage of a people’s and its
culture’s development.
Thus, until the second half of the 19th century, the concept of culture was rarely
used and almost exclusively in the German language. Only in 1871 did the English
anthropologist E. B. Tylor provide a classical, fully modern definition of culture in his
monograph Primitive Culture: “complex whole which includes knowledge, belief, art,
law, morals, custom, and any other capabilities and habits acquired by man as a member
of society” [112]. He also introduced the word culture into the English language. It is
worth noting that Tylor, like many of his predecessors, viewed the concepts of culture
and civilization as synonymous.
Towards the end of the 19th century, in addition to the first meaning of culture as
an individual level of education and development, and the second meaning as an (almost)
synonym for civilization, a third—anthropological—definition emerged: culture as a
tradition transmitted through social inheritance.
The English poet T. S. Eliot dedicated a special essay to the problem of defining
culture, where he identified these three dimensions of culture. Eliot wrote that culture
could be used in three senses: as a characteristic of an individual, as a characteristic of a
group or class, and as a characteristic of an entire society [41].
In their classic 1952 work, A.L. Kroeber and C. Kluckhohn presented several
dozen definitions of culture, grouped into six categories [cited in 66]:
1) Descriptive definitions: These include Tylor’s definition and all definitions that
echo it, such as R. Benedict’s “complex whole which includes all the habits acquired by
men as a member of society”; F. Bose’s “crystallized phase of man’s life activity (…)
habitual attitudes of mind transferable from one person to another”; and B. Malinowski’s
“the interal whole consisting of implements and consumers’ goods, of constitutional
charters for the various social groupings, of humаn ideas and crafts, beliefs and
customs”.

12
2) Historical definitions with an emphasis on inheritance and tradition: E. Sapir
defined culture as “any socially inherited element in the life of man, material and
spiritual”; C. Kluckhohn described it as “the social legacy the individual acquires from
his group”;
3) Normative definitions, which emphasize conformity to behavioral norms and
values: C. Wissler called culture “the mode of life followed by the community or the
tribe (…) the aggregate of standardized beliefs and procedures”; R. Linton defined it as
“the collection of ideas and habits which they [society members] learn, share, and
transmit from generation to generation”; and W. Thomas referred to it as “the material
and social values of any group of people, whether savage or civilized (their institutions,
customs, attitudes, behavior reactions)”;
4) Psychological definitions: R. Benedict defined culture as “learned behavior,
behavior which in man is not given at birth, which is not determined by his germ cells as
is the behavior of wasps or the social ant, but must be learned anew from grown people
by each new generation”; K. Young described it as “forms of habitual behavior common
to a group, community, or society. It is made up of material and non-material traits”; and
G. Roheim referred to it as “the sum of all sublimations, all substitutes, or reaction
formations, in short, everything in society that inhibits impulses or permits their
distorted satisfaction”;
5) Structuralist definitions: C. Kluckhohn and W. Kelly described culture as “a
historically derived system of explicit and implicit designs for living, which tends to be
shared by all or specially designated members of a group”;
6) Genetic definitions, which focus on the origin of culture: P. Sorokin defined it
as “the sum total of everything which is created or modified by the conscious or
unconscious activity of two or more individuals interacting with one another or
conditioning one another’s behavior”; W. Ostwald described it as “That which
distinguishes men from animals”; and R. Bain considered it as “all behavior mediated by
symbols”.

13
To these definitions, we add some notable definitions from the second half of the
20th century.
The founder of ethnometry, G. Hofstede, viewed culture as “the collective
programming of the mind which distinguished the members of one human group from
another” [48, p. 21]. According to Kroeber and Kluckhohn’s classification, this
definition can be considered structuralist.
The American biologist E. O. Wilson, a founder of sociobiology—the study of
social behavior in humans and animals from the perspective of evolutionary
theory—wrote that “culture, including the more resplendent manifestations of ritual and
religion, can be interpreted as a hierarchical system of environmental tracking devices”
[116]. This definition aligns with Kroeber and Kluckhohn’s genetic classification.
The English evolutionary biologist R. Dawkins, in his book The Selfish Gene,
introduced the concept of a meme—the elementary unit of cultural information
(analogous to the gene as the elementary unit of hereditary information). Without
providing a formal definition of culture, Dawkins viewed culture as an integral entity
similar to a genome, consisting of individual ideas, behavioral patterns, and styles that
are inherited from one person to another, may undergo “mutations,” and evolve and
change [7].
1.2. Major Approaches to Cross-Cultural Comparisons
In the early stages of philosophical and scientific thought in antiquity, the primary
reasons for differences between peoples were attributed to the level of their development
(Democritus, Lucretius), the influence of the natural environment, particularly
geographical factors (Hippocrates, Aristotle), or mutual cultural influences (Herodotus,
Strabo) [6].

14
During the Enlightenment, C.-L. Montesquieu expanded on Hippocrates and
Aristotle's ideas about the role of geographical factors and climate in creating
differences among peoples. He proposed that less developed peoples are more dependent
on environmental factors, which, in turn, have a greater influence on their “general
spirit” (a term used by Montesquieu that resonates with later concepts such as “national
spirit” or “national soul,” often equated with the notion of national psychology). In
contrast, higher nations depend more on social factors in their development [19].
D. Hume was perhaps the first to use the concept of “national character” to
explain differences among peoples. He concluded that this characteristic depends
primarily on the socio-political factors of a society’s life, as well as on its morality and
accepted rules of behavior.
In the second half of the 19th century, evolutionists (E. Tylor, H. Spencer, L.
Lévy-Bruhl), under the influence of Darwin's theory of evolution, sought to study the
origins and development of beliefs and marriage. This direction is often referred to as
linear evolutionism, likely highlighting its overly mechanistic view of cultural evolution.
Evolutionists divided all peoples into primitive and advanced.
During the same period, functionalists (E. Durkheim, B. Malinowski, A.
Radcliffe-Brown) examined differences in the material culture of various peoples and
the structure of their groups. As the name suggests, functionalists viewed culture as an
integral entity composed of individual elements, each performing a specific social
function.
An important stage in the development of a scientific approach to cultural
comparison was the emergence of the so-called folk psychology (Völkerpsychologie) in
the second half of the 19th century. Essentially, this marked the differentiation of a
distinct scientific discipline, later known in the European tradition as ethnic psychology.
The emergence of folk psychology is primarily associated with M. Lazarus and H.
Steinthal. These researchers saw differences among peoples in the “national spirit,” a
certain phenomenological entity that is constant and immutable for a given people and

15
can be understood through the study of its mythology, morality, and language [6].
The founder of modern experimental psychology, W. Wundt, was also interested
in psychological explanations of ethnological phenomena, culminating in his ten-volume
work Völkerpsychologie. He identified the "national soul" as the primary feature
distinguishing one ethnic group from another, which could be understood through
language, myths, and customs [18]. Interestingly, Wundt attempted to bridge the gap
between individual psychology and folk psychology, combining cultural and individual
levels of analysis—a task that would later be revisited by other researchers after the
establishment of ethnometry in the second half of the 20th century. However, Wundt
approached this task rather mechanistically, postulating that language, as a cultural
element, is identical to reason at the individual level, customs are identical to will, and
myths to feelings. Furthermore, Wundt believed that cultural phenomena cannot be
studied experimentally, unlike individual psychological processes [6].
At the end of the 19th century, G. Le Bon used terms such as “the soul of races”
and “national soul” as key features for classifying nations. He explored the relationship
between the individual and the collective and raised questions related to psychogenesis.
It should also be noted that from antiquity, there was a process of formally
describing various peoples, their way of life, unique aspects of their existence, origins,
and elements of their material and spiritual culture. This area of research, in the 19th
century, came to be known as “ethnography” (or “ethnology,” which is considered
synonymous or at least closely related). To this day, it remains closely intertwined with
ethnic psychology and anthropology. Interestingly, 19th-century German science
developed two types of ethnography: one that studied its own people and another that
studied all other peoples. This approach was also characteristic of French ethnography.
Also, the development of anthropology cannot be overlooked. This is another
discipline closely and intricately connected with psychological studies of peoples and
cultures. In a broad sense, anthropology is a complex of disciplines studying humans,
including their biological essence and processes of socio- and cultural genesis. This

16
broad view of anthropology is accepted in Western scientific tradition, whereas in the
USSR and post-Soviet countries, anthropology was understood merely as “physical
anthropology” (also known as “biological anthropology”), a natural science about the
structure and origin of humans as biological beings.
The term “anthropology” emerged during the Renaissance and initially referred to
the science of humans, but until the 19th century, the discipline was closely associated
with philosophy (for example, Kant's classical work, which had no direct relation to
scientific anthropology, was titled Anthropology from a Pragmatic Point of View). In the
19th century, the term “cultural anthropology” began to denote a complex of humanities
disciplines related to the study of humans (ethnography, folklore studies, even linguistics
and archaeology) and aimed at exploring cultural diversity. A related term, “social
anthropology,” came to refer to the study of social structures and relationships between
people. The combination of these sciences, aimed at clearly distinguishing them from the
methodologically separate natural science of physical anthropology, became known as
“sociocultural anthropology” [6; 18].
Following these phenomenological generalizations, which developed from
antiquity to the late 19th century, predominantly in the United States, purely scientific
directions based on the empirical study of various cultures emerged in the early 20th
century. Thus, ideas about national character, national spirit, and national soul—complex
and poorly understood entities practically inaccessible to empirical study—were
replaced by empirical studies of cognitive processes, the Oedipus complex, child-rearing
styles, and more. These scientific studies developed within four schools: “Culture and
Personality” (later known as psychological anthropology), cross-cultural psychology,
cultural psychology, and indigenous psychology.
The main subject of psychological anthropology (notable figures: R. Benedict, F.
Boas, A. Kardiner, R. Linton, M. Mead, M. Spiro) was the study of mental processes
(thinking, emotions, perception) within different cultural contexts.
Psychoanthropologists abstracted from culture in general, culture as a universal social

17
phenomenon, and instead focused on specific cultures, striving to describe and
characterize as many diverse cultures as possible. In its early stages, this field was called
the “Culture and Personality” school, reflecting the dual nature of its methodological
approach, namely, the combination of psychological and ethnological data [70].
Cross-cultural psychology (notable figures: M. Bornstein, M. Herskovits, W.
McDougall, W. Rivers, M. Segall), closely related to psychological anthropology, is best
regarded as a methodological approach rather than a distinct field [18]. It emphasizes
identifying psychological similarities and differences among individuals from different
cultural and ethnic groups, particularly in the search for cultural universals. By studying
a single psychological variable across different cultures, cross-cultural psychology
compares and contrasts these cultures.
Cultural psychology (notable figures include L. Vygotsky, M. Cole, A. Luria, and J.
Miller) studied personality in sociocultural and historical dimensions, attempting neither
to contrast nor compare cultures based on any predetermined criteria, which
distinguishes it from cross-cultural psychology. Thus, cultural psychology resembles an
eclectic research direction, synthesizing approaches from the previous two fields without
a clearly defined scientific paradigm.
Indigenous (multicultural) psychology (notable figures: F. Sahoo, D. Sinha) seeks
to understand the diversity of distinct and unique psychologies of the world’s numerous
cultures. According to this field’s proponents, each culture is a unique and unparalleled
phenomenon that can only be fully understood from within [6].
1.3. Development of Ethnometric Research
Ethnometry is a methodological approach within cross-cultural psychology based
on the quantitative measurement of cultural components. Its history begins with the
work of the Dutch psychologist G. Hofstede, who conducted a study between 1967 and

18
1973 among IBM employees in more than 70 countries, surveying over 100,000
respondents using a questionnaire he developed [48; 49].
It should be noted that the term “ethnometry” is used only in the post-Soviet space
and is not entirely accurate for this field of research. Quantitative methods in
cross-cultural studies were employed even before Hofstede, for example, in studies of
cognitive processes across different peoples. Hofstede's primary contribution lies not in
being the first to “measure cultures,” as some authors believe (although, undoubtedly,
after his work, quantitative methods became dominant in cross-cultural psychology), but
in his novel approach to defining the components of culture—determining what exactly
should be compared in cross-cultural studies to ensure valid and reliable results.
According to Hofstede, the answer is as follows: one should compare the factors that
emerge in the factor analysis of responses from representatives of different cultures.
Hofstede identified four such factors (so-called “cultural values”) [48]: 1)
Individualism (IND) (opposite: collectivism) – the degree to which personal goals are
prioritized over group goals; 2) Power Distance Index (PDI) – the extent to which
members of a society accept unequal power distribution; 3) Masculinity (MAS)
(opposite: femininity) – the level of assertiveness and display of “masculine” traits such
as competitiveness and determination; 4) Uncertainty Avoidance Index (UAI) – the
degree to which people tolerate and respond to unfamiliar situations.
In the late 1980s, as a result of measurements conducted in China, a fifth
dimension was added: Long-Term Orientation (LTO) [50] – an orientation toward
strategic goals and a focus on the future. A sixth dimension, Indulgence vs. Restraint
(IVR), was introduced in 2010 based on data from the World Values Survey [72]; this
dimension measures the extent to which a society allows relatively free gratification of
human desires related to enjoying life. Recently, in 2011, the construct of
Tightness-Looseness was introduced, based on cross-cultural studies of 33 countries; it
characterizes the strength of social norms and the tolerance for their violation [40].
Numerous cross-cultural studies using Hofstede's methodology in dozens of

19
countries revealed that individualistic cultures are primarily characteristic of Western
countries, while collectivist cultures dominate in Eastern countries and Africa. Power
Distance also divides countries into two groups—Western and Eastern. For Long-Term
Orientation, high scores are typical only for East Asian countries with Confucian
traditions. The polarization of other Hofstede indices is less pronounced.
After Hofstede, other major cross-cultural projects included: Schwartz's project,
which identified seven cultural dimensions [89]; the Smith, Dugan, and Trompenaars
project, which analyzed 43 countries and identified two dimensions [97]; the GLOBE
project, which studied 62 countries and identified nine dimensions [52]; the World
Values Survey (WVS), the largest ongoing project, which has examined around 70
countries [126].
Many of the “new” dimensions identified in these projects correlate with
Hofstede's dimensions, which are now considered fundamental and used to validate
cross-cultural research results.
In cross-cultural studies, the concept of social axioms has also been introduced to
complement Hofstede’s cultural dimensions, describing beliefs about how the world and
society function [38]. There are five axiom groups: social cynicism, social complexity,
reward for application, religiosity, and fate control.
In most cross-cultural studies, the primary focus has been on the construct of I-C,
considered the most significant indicator of cultural variability and the “main dimension
of cultures” [18]. Comprehensive development of this concept by scholars such as
Hofstede, Triandis, and Kim laid the foundation for modern cross-cultural psychology.
1.4. Individualism-Collectivism as a Fundamental Cultural Dimension
The history of philosophical and scientific thought shows that the development of
the concepts of individualism and collectivism spans at least a century. For example, the

20
founder of modern sociology, É. Durkheim, introduced the terms “organic” and
“mechanical” solidarity in 1887. The former describes temporary connections between
dissimilar members of modern societies, while the latter refers to permanent bonds
among similar members of traditional societies [8]. In 1905, German sociologist M.
Weber contrasted the individualistically oriented Protestantism with the collectivistically
oriented Catholicism [3]. Another notable sociologist, G. Le Bon, in 1908 considered
individualistic cultures superior, stating: “The peoples among whom Individualism is
most highly developed are by this fact alone at the head of civilisation, and today
dominate the world.” [16, p. 50].
Systematic scientific study of these phenomena began in the 1930s. In the
mid-20th century, American anthropologist Margaret Mead emphasized that cultures
vary in their emphasis on cooperation, competition, and individualism [70]. However, it
wasn’t until the 1970s that a methodological framework for quantitatively measuring I-C
was developed.
Following Hofstede's ethnometric studies, individualistic cultures came to be
understood as those where individuals prioritize themselves and their immediate family,
while in collectivist cultures, people often belong to groups beyond the family (so-called
in-groups) and primarily identify themselves as members of these groups. This
distinction also affects workplace relationships (the main focus of Hofstede’s research):
in individualistic societies, workplace connections are more distant, and career
advancement is based on competence, while in collectivist societies, a sense of duty and
loyalty to the organization play a decisive role; relationships are built on personal
connections, and career progression depends on seniority [49].
Harry Triandis significantly reinterpreted this construct by introducing the concept
of cultural syndromes. He argued that collectivism is most prominent in simple, and
relatively high-density societies, whereas individualism tends to prevail in complex and
loose societies [105, 4]. Triandis also focused on the characteristics of in-groups.
Individualistic and collectivistic cultures differ in the number of in-groups:

21
individualistic cultures have many diverse in-groups (reflecting the complex structure of
society), which exert less influence on individuals than the few primary in-groups found
in collectivist cultures. This might explain why Western societies have so many political
parties, associations, and unions that exert relatively weak influence on individuals;
people freely change groups depending on their interests and remain independent of
them [106].
After Triandis, this construct was further developed by U. Kim, Ç. Kağitçibaşi,
and J. Berry [9]. Bulgarian sociologist M. Minkov offered a more recent reinterpretation,
suggesting that the I-C construct is overly broad and imprecise. He proposed the term
Exclusionism-Universalism [72], which has yet to gain widespread acceptance.
1.5. Ukrainian Culture: Individualism or Collectivism?
In popular belief, individualism is considered one of the defining characteristics of
the Ukrainian mentality. Consider the well-known proverbs: “My house is at the edge”
and “One’s own shirt is closer to the body”. Prominent Ukrainian scholars of Ukrainian
studies have pointed to Ukrainian individualism: M. Kostomarov, for instance,
highlighted the “separation” of adult children from their parents [12], while D.
Chyzhevsky described it as a desire for freedom that, in some cases, “leads to
self-isolation and conflict with everything and everyone” [25].
At the same time, many researchers emphasize that Ukrainian culture has deep
collectivist traditions. This is evidenced, for example, by the absence in the Ukrainian
language—and in all East Slavic languages—of an equivalent for the English term
“privacy”, a cornerstone of individualistic culture [92]. However, the re-evaluation of
cultural values in terms of I-C in Ukraine has been ongoing for centuries. It began in the
religious-polemical literature of the 16th century and took on a passive-contemplative

22
character after Ukraine became part of the Russian Empire, as seen in the contradictory
views of H. Skovoroda [11].
It is believed that collectivist values dominated in the Soviet Union, as suggested
by a 1985 study (cited in [107]). However, F. Trompenaars and C. Hampden-Turner,
who developed their own concept of cultural differences, classified the USSR and
Czechoslovakia as individualistic rather than collectivist [109].
Given the somewhat contradictory data on this issue, it is possible that Ukrainian
culture, in terms of the I-C dimension, represents a typical borderline culture, which
cannot be unequivocally classified as either individualistic or collectivist. Other
examples of such cultures include those of Israel and India—complex mixtures of
individualistic and collectivist traditions that, nonetheless, coexist quite successfully
[95].
Employing an ethnometric approach to studying Ukrainian culture could shed
light on whether Ukrainians lean more toward individualistic or collectivist orientations.
1.6. Ethnometric Studies in Ukraine
В Україні найбільше етнометричних досліджень проводилося з
використанням методики Хофстеде. Проте, оскільки автори користувалися різними
варіантами опитувальника, їхні результати, на жаль, практично неможливо
порівняти між собою. At the same time, only three Ukrainian studies adhered to the
principles of cross-cultural research, as they included comparisons of multiple countries
(more than 10, according to Hofstede's recommendation).
Ukrainian scores for IND, PDI, and LTO in these studies were close to average
values [98; 99; 103]; the MAS index was either very low [99] or relatively high [103],
while the UAI index was high [99; 103].

23
Two other studies compared different regions of Ukraine. Western Ukrainians
showed lower PDI, LTO, and UAI scores [20; 26]. For the other three indices, the data
were inconsistent: IVR showed either no differences [26] or lower scores in the East [20];
MAS was either higher in the West [26] or in the East [20]; IND was either higher in the
West [26] or showed no significant differences [20].
Another issue with using Hofstede’s approach is that some authors ignore the fact
that the indices are relative and only make sense when comparing multiple cultures, not
on their own [48]. As a result, they unjustifiably draw conclusions about the index value
for Ukrainians without cross-cultural comparison [20]. Additionally, some authors
compare indices of organizations [14], even though Hofstede’s scale was not designed
for this purpose at all.
Three studies used other scales and focused solely on the I-C dimension. A
comparative study of Ukrainians and Americans using a short version of Triandis’s
14-item scale [106] found that Ukrainians displayed stronger individualism [92].
Another comparative study, using the full version of the Singelis et al. scale [51], yielded
entirely opposite results [75]. The most recent study from 2016 (based on 1999 data)
showed that individualism was more pronounced in Western Ukraine than in Eastern
Ukraine [60]; the authors used a scale assessing self-construal [94].
Other studies of Ukrainian culture have measured social axioms. It was found that
Ukrainians are more likely than people from other countries to have a negative view of
human nature (second place in the “social cynicism”), exhibit low social complexity
(last place), and believe that life events are predetermined by fate, with little under
individual control (first place in “fate control”) [22].
Regarding the Tightness-Looseness construct, Ukrainians received the lowest
score among the 33 studied countries, characterizing Ukrainian culture as very “loose,”
with weak social norms and high tolerance for norm violations [40].
Studies on value orientations have shown that Ukrainians prioritize
self-enhancement values such as success, work, career, respect, and self-esteem; key

24
features of Ukrainian culture include introversion and a focus on personal relationships
(love, fidelity, and a happy family life) [2].
When compared to other European countries using Schwartz’s values, Ukrainians
displayed extreme scores [21; 93]. For example, Ukrainians scored higher than other
Europeans in Conformity, Power, and Tradition . Security was the most important value
for Ukrainians, while Hedonism and Stimulation were the least important, in contrast to
other Europeans, who prioritized Universalism and Benevolence while placing the least
importance on power and Stimulation [21].
Based on Schwartz’s value studies, Rudnev and Magun paint the following
unflattering portrait of the average Ukrainian: «......a person characterized by
considerable caution (or even fear), a need for protection from a strong state,
conservatism, and fear of social disapproval. Consequently, this person has weak needs
for novelty, creativity, freedom, and independence, lacks a propensity for risk-taking,
and avoids seeking pleasure and entertainment. At the same time, this person aspires to
wealth and power, as well as personal success and social recognition... A strong
orientation toward individual self-assertion reduces their willingness to care even for
those directly around them» [21].
According to the Big Five Personality Inventory, Ukrainians demonstrate high
Introversion (only five countries out of 56 scored lower), low Agreeableness (the lowest
score among all studied countries), fairly low Conscientiousness (only eight countries
scored lower), low Openness to experience (only two countries scored lower), but
relatively high Emotional stability (only eight countries were more stable) [86].
Finally, the previously mentioned study [98] showed that the locus of control
indicator among Ukrainians is at a rather low level (lower in only two out of 24
countries), which indicates its internality.
Ethnometry as a method of cross-cultural psychology has been developing for
almost half a century, but ethnometric research in Ukraine is still in its infancy.
Ukrainian mentality, characterized by the coexistence of diverse and sometimes

25
contradictory cultural norms and attitudes, could offer significant insights for
cross-cultural psychology and contribute to a better understanding of the emergence and
evolution of cultural universals.
1.7. The Structure of Individualism-Collectivism
G. Hofstede initially viewed I-C as a unidimensional bipolar construct—meaning
that measuring individualism alone was sufficient, as collectivism would be reflected in
low individualism scores [48]. Over time, it became evident that I-C (more precisely,
individualism and collectivism) are two separate, complex, and non-mutually exclusive
constructs. A person can exhibit both individualistic and collectivistic tendencies
simultaneously, and their orientation may vary situationally, depending on the social
context (reviewed in [78]).
Triandis proposed a four-dimensional model instead of a two-dimensional one,
introducing two new dimensions: horizontal and vertical. These four combinations yield
four types of national cultures [51]: 1) Horizontal Individualism – characterized by
independence, uniqueness, autonomy, equality, and a lack of interest in high social status
(e.g., Sweden); 2) 2.Vertical Individualism – marked by independence and autonomy in
a hierarchical world, with competition and a desire for higher social status (e.g., the
United States); 3) Horizontal Collectivism – belonging to groups whose members are
equal (an ideal scenario, not typical for entire countries—e.g., an Israeli kibbutz); 4)
Vertical Collectivism – belonging to groups with members of differing statuses and a
willingness to selflessly submit to authority (e.g., Russia).
Triandis’s work laid the groundwork for a more detailed exploration of the
structure of I-C. Kim [62] conceptualized I-C as a six-factor model, where both
individualism and collectivism consist of three factors (referred to as “modes”). Chen et

26
al. [32] also favored a six-factor model, further subdividing Vertical and Horizontal
Collectivism into two additional factors. Jackson et al. [56] viewed collectivism as a
five-dimensional construct. Roccas et al. [83] approached the structure of I-C as a
broader issue of group identity. Their multidimensional model of group identity includes
I-C alongside identification with various social groups and the nation (manifested as
nationalism and patriotism). A. Realo and J. Allik [81] identified three forms of
collectivism organized hierarchically: connection with family (familism), friends or
colleagues (sociability), and society (patriotism). Gelfand et al. [45] distinguished two
types of collectivism: institutional collectivism (the degree to which societal institutions
encourage and reward collective behavior) and in-group collectivism (traditional
collectivism, which reflects the strength of ties between individuals, their families, and
other social groups).
It is worth noting that in these models, individualism and collectivism are often
viewed not as cultural-level attributes but as constructs at the personality level. Triandis
and colleagues [108], aiming to integrate different levels of studying I-C, introduced the
concepts of allocentrism and idiocentrism, which are personal dimensions of
collectivism and individualism, respectively.
When considering the two most popular I-C models—Hofstede’s and
Triandis’s—it is essential to note that neither dominates contemporary cross-cultural
psychology [78]. They coexist, with different research groups selecting a model based
on their preferences and theoretical inclinations. The uncertainty is compounded by the
existence of Schwartz’s value model. Initially developed as a ten-factor model for
individual-level analysis, subsequent studies have shown that at the national level, this
model exhibits a stable seven-factor structure, which can also be effectively used for
cross-cultural comparisons [89]. Schwartz’s model is considered broad, encompassing
all the dimensions underlying Hofstede’s and Triandis’s models [89; 100].

27
1.8. Temporal Dynamics of Individualism-Collectivism
Cultural products are an extremely promising subject for psychological research.
Renowned experts in cultural psychology, H.R. Markus and S. Kitayama, emphasized
the reciprocal influence of culture and personality: personality changes cultural products,
but culture also influences personality and transforms it [69].
Among numerous cultural products, printed literature represents perhaps the best
resource for studying cultural changes. Culture is inseparable from language and is
transmitted through language. In printed literature, linguistic and cultural traits of people
who lived in different times are recorded, which is why studying printed sources
provides us with a key to understanding the causes and dynamics of cultural
transformations.
Pronouns are an important object for studying the dynamics of linguistic changes
since they are relatively stable, unchanging linguistic units that are also linked to
individualistic and collectivist cultural values. Experimental research has shown that
first-person singular pronouns activate individualistic values [44]. Activation of
self-awareness through a camera or mirror makes a person think that the pronouns they
need to guess are first-person singular pronouns [39]. Representatives of collectivist
cultures are more inclined to think that an unknown pronoun to guess is a plural pronoun
[76].
Therefore, it is now undeniable that first-person singular pronouns ('I' and its
derivatives) are associated with an individualistic orientation, as they emphasize a
person’s individuality and sense of self. First-person plural pronouns ("we" and
derivatives) are associated with collectivist orientation, as they shift the focus of
attention toward the group. Second-person pronouns ("you" and derivatives) are also
linked to individualism, as they are meant to separate the subject from others [111].
Until recently, studying cultural changes through content analysis was an

28
extremely difficult task, requiring the combined efforts of large groups of researchers or
was limited to narrow tasks. For example, such research might have been confined to
studying collectivist and individualistic values in school textbook stories [55],
examining cultural differences in the presentation of criminal reports in newspaper
articles [74], etc. With the emergence of large linguistic corpora in the 21st century, the
situation has radically changed.
A linguistic or text corpus is a systematically selected and annotated collection of
texts that can be used for large-scale statistical research and is designed to reflect as
accurately as possible the natural features of a given language. In recent years,
specialists in corpus linguistics have created several national linguistic corpora, but the
most popular and extensive remain the text corpora of Google (Google Books Ngram),
dated 2009-2012 [80]. The Google Books Ngram database contains more than five
million books (6% of all books ever printed) [80], representing the eight most widely
spoken languages in the world.
After 2009, when the first version of Google Books Ngram appeared, several
studies were dedicated to exploring the dynamics of I-C using this linguistic corpus.
Twenge et al. studied the dynamics of the use of all personal and possessive
pronouns in the sub-corpus of American English for 1960-2008 [111]. They showed that
the use of first-person singular and second-person pronouns increased by 42% and 300%,
respectively, while the use of first-person plural pronouns decreased by 10%.
The same authors, using the sub-corpus of American English for 1960-2008, also
studied the dynamics of the use of individualistic and collectivist words and phrases
[110] and concluded that the former noticeably increased in usage during the study
period.
Twenge et al.'s work prompted the study of other languages. In 2014, Uz [113]
studied all nine languages represented in Google Books Ngram. This study is of special
interest because the author aimed to establish a link between the dynamics of pronoun
usage in a given language and the individualism index of the corresponding country,

29
based on Hofstede’s work. It was shown that there is a significant positive correlation
between the relative frequency of first-person singular pronouns (compared to
first-person plural: (I+me)-(we+us)) and Hofstede’s index.
In 2016, a group of researchers [36] showed that for eight of the nine languages in
Google Books Ngram (except British English), the relative frequency of first-person
singular pronouns (compared to first-person plural: (I+me)-(we+us)) significantly
increased from 1949 to 2008, and all trends were nonlinear, quadratic (U-shaped).
Finally, another study from last year [96] focused on the use of individualistic and
collectivist words in the Russian sub-corpus of Google Books Ngram over the period
1901-2009, as well as their connection to economic indicators. The results show an
increase in the use of only individualistic words during the study period, while the use of
collectivist words remained almost unchanged.
Thus, the study of the temporal dynamics of cultural value changes is a young and
promising direction for psychological research. The reviewed works have demonstrated
a general trend toward the growth of individualistic orientation in the world since the
mid-20th century.

30
CHAPTER 2
METHODOLOGICAL JUSTIFICATION AND
PROCEDURE FOR EMPIRICAL RESEARCH
2.1. Methods and Stages of Studying the "Spatial" Characteristics of
Individualism-Collectivism
2.1.1. Selection of the Scale
The issue of selecting an appropriate empirical toolkit is highly relevant. The issue
of choosing an adequate empirical tool is extremely relevant. As evidenced by the
analysis of ethnometric studies in Ukraine, the contradictory results obtained are largely
due to the lack of reliable and valid Ukrainian-language scales. Among approximately
30 scales for measuring I-C [78], there is no universally accepted standard, which is why
different scales can yield completely opposite results.
Various versions of the historically first Hofstede’s scale are a popular tool for
cross-cultural studies, including those conducted in Ukraine, but this scale is designed to
assess all cultural values, not just I-C. Moreover, as some authors note [99], Hofstede's
tool is characterized by low reliability. As the author himself emphasizes [48], his scale
is intended only for cross-cultural studies of two or more countries (optimally - 10); in
the worst case, the scale can be used to study regional differences in large culturally
heterogeneous countries.
Scales developed by G. Triandis' school have broader applicability, allowing the
identification of both vertical and horizontal components of I-C, and are sufficiently
valid and reliable [34]. The main one in this series is the scale proposed by Singelis,
Triandis, Bhawuk, and Gelfand in 1995 [51]. It is the second most frequently used after
Hofstede's scale [102], and it has been widely adapted for conducting cross-cultural

31
research—there are versions in Spanish [47], Italian [28], Korean [82], and others;
furthermore, in several countries, the original untranslated version has been used. For
these reasons, for our research, we decided to choose the Singelis et al. scale.
2.1.2. Ukrainian Adaptation of the Singelis et al. (1995) Scale
None of the scales used in Ukraine for ethnometric studies have been adapted for
use specifically in Ukraine. Only some of them (e.g., the Hofstede scale) have been
translated into Ukrainian. The validity and reliability of any scale have also not been
studied in Ukraine. Therefore, our first task was to conduct a Ukrainian-language
adaptation of the Singelis et al. (1995) scale, including its translation and research on its
validity and reliability1.
The translation of the scale from English to Ukrainian was done using the
back-translation method. Initially, the translator aimed to convey the meaning of each
statement as accurately as possible while ensuring that it was understandable to a
Ukrainian user. Then, the first version of the Ukrainian text was translated back into
English, compared with the original English version, and necessary corrections and
clarifications were made. The translation was done by a professional translator with the
involvement of a psychologist fluent in both English and Ukrainian.
As a result of applying this approach, the following Ukrainian-language version of
the scale was obtained:
1. Розмовляючи з людьми, я надаю перевагу прямолінійному, відвертому
спілкуванню
2. Моє щастя значною мірою залежить від щастя людей, що мене оточують
3. Я б робив те, що подобається моїй сім’ї, навіть якби терпіти не міг цієї
справи
4. Перемога - це все!
5. Кожен повинен жити, не залежачи від інших
1adapted with written permission from SAGE Publications, the copyright holder

32
6. За все, що відбувається зі мною, несу відповідальність лише я
7. Як правило, я жертвую своїми власними інтересами (вигодою) на користь
групи, до якої належу
8. Мене дратує, коли хтось виконує роботу краще за мене
9. Для мене важливо, щоб у групі\групах, до яких я належу, підтримувалися
гармонійні стосунки
10. Для мене важливо робити свою роботу краще за інших
11. Я люблю ділитися різними дрібничками зі своїми сусідами
12. Мені подобається працювати в атмосфері конкуренції
13. Наші старенькі батьки мають жити разом з нами в одному домі
14. Благополуччя моїх колег по роботі важливе для мене
15. Мені подобається бути унікальним, багато в чому несхожим на інших
людей
16. Якби мій родич опинився у фінансовій скруті, я б допоміг йому у міру
своєї можливості
17. Діти повинні пишатися своїми батьками, якщо ті отримують заслужену
винагороду (похвалу, визнання)
18. Мої інтереси і те, що я роблю в житті, стосуються лише мене
19. Конкуренція - це закон життя
20. Якщо мій колега по роботі отримає премію, я буду радий за нього
21. Я - унікальна людина
22. Задоволення для мене - це проводити час з іншими людьми
23. Коли хтось робить роботу краще за мене, я внутрішньо напружуюся і
мобілізуюся
24. Я б пожертвував справою, яку я дуже сильно люблю, якщо б цю справу
не схвалювала моя сім’я
25. Мені подобається приватність
26. Хороше суспільство неможливе без конкуренції

33
27. Дітей треба вчити ставити на перше місце свої обов’язки, а не власні
забаганки
28. Я почуваюся прекрасно, коли виконую з іншими якусь спільну роботу
29. Терпіти не можу, якщо доводиться не погодитися із іншими членами
групи, до якої я належу
30. Деяким людям важливо постійно перемагати, але я не один з них
31. Перед тим, як вирушити в далеку поїздку, я раджуся з багатьма своїми
рідними і друзями
32. Коли я досягаю успіху, це, як привило, пояснюється моїми здібностями
33. Я - віруюча людина
34. Я пишаюся тим, що я українець/українка
35. Я пишаюся українською історією
36. Я відчуваю близькість, міцний зв'язок з моєю безпосередньою сім'єю
(дітьми, чоловіком\дружиною, батьками)
37. Я відчуваю близькість, міцний зв'язок з більш далекими родичами
(бабусею, дідусем, тіткою, дядьком і т.д.)
38. Я відчуваю близькість, міцний зв’язок з моїми друзями
39. Я відчуваю близькість, міцний зв'язок з людьми, що оточують мене в
повсякденному житті (колегами по роботі, членами громади, сусідами і т.д.)
40. Я пишаюся українським демократичним державним устроєм
41. Я пишаюся українською системою соціального захисту
Questions #33-41 were added for additional research into the validity of the scale
and to check for important correlations. These include questions where participants had
to assess the degree of their connection to various in-groups (family, relatives, friends,
coworkers, and neighbors), as well as questions to assess nationalism (No. 33, 34) and
patriotism (No. 40, 41). The questions to assess nationalism and patriotism were taken
from the work of [115]; the authors, in turn, obtained them from more extensive scales,
which showed that these four questions best load onto the nationalism and patriotism

34
scales in factor analysis.
For the purposes of our research, an online survey was of the greatest interest, as it
allows for surveying a significant number of respondents from different regions of
Ukraine in a short period. The number of psychological studies using the Internet has
been increasing every year. For example, data obtained through the popular Internet
platform Amazon Mechanical Turk are published in leading scientific journals. In this
regard, much attention has been paid to the problems of validity and reliability in
psychological testing over the Internet. As thorough comparative analyses show, the
results of Internet-based studies do not differ from those of traditional approaches using
paper formats, except that more attention must be paid to the problem of multiple
responses from a single user [30; 46]. Regarding the use of ethnometric tools in online
surveys, there are very few such studies, but a few works [67] allow for concluding that
this approach has great potential.
Taking these considerations into account, we decided to create an electronic
version of the scale and conduct the survey via the Internet. Using the online service
Google Forms, we created an interactive electronic version of the scale, which allowed
the user to see their score for the individualism and collectivism scales after answering
all the questions, which would stimulate interest in the survey. The recommended order
of statements was not specified in the original publication, but some other authors paid
attention to this issue. We used the order of statements recommended by the developers
of the Danish [77] and Italian [28] versions of the scale.
All questions were to be rated on a 9-point scale from 1 (strongly disagree) to 9
(strongly agree). The statements to assess religiosity were accompanied by a separate
explanation: “rate your level of religiosity from 1 (strongly no, I am completely
indifferent to religion) to 9 (definitely yes, I am a very religious person)” («оцініть міру
Вашої релігійності від 1 (категорично ні, я повністю байдужий до релігії) до 9
(безумовно так, я дуже віруюча людина))». At the end of the survey, participants were
asked to indicate their age, gender, the language they use in daily life, where they spent

35
most of their life (select the region), where they currently live (select the region), and
whether they live in a city or a village.
The survey was conducted in April and August 2016 using the electronic version,
which was distributed via email (through personal invitations to participate in the study)
and by posting an announcement on thematic Ukrainian forums on the Internet. Each
participant could only take the survey once. After receiving the responses, the scores on
the Individualism, Collectivism, VI, HI, VK, and HK scales were summed according to
the key (see Table 3.2). It is important to note that question #30 is reverse-coded (the
sum of the scores for this type of question needs to be transformed before beginning
statistical analysis).
The following stages of adaptation included studying construct validity using CFA
and reliability using Cronbach's alpha method. In the first case, the lavaan package [84]
for the R programming environment was used, and in the second, SPSS 17.0 software
was used. CFA was conducted using the maximum likelihood (ML) method. Since this
method is intended for normally distributed data, the Satorra-Bentler test was also
conducted, which adjusts for non-normal distribution.
2.1.3. Processing of Survey Results
As a result of the survey, we collected the sum of scores across six scales, taking
into account age, gender, region of residence, and language of communication. These
data were processed using standard mathematical statistics methods, compared among
each other, and with the sum of scores that reflected the strength of the connection with
a particular in-group and the score on the "religiosity" scale.
The statistical processing of this data involved methods such as descriptive
statistics (mean, standard deviation, tests for normality, homogeneity of variance, and
the presence of outliers), methods for comparing means (Student's t-test, Mann-Whitney
test, analysis of variance), and methods of correlation analysis (Pearson's correlation,
Spearman's correlation, multiple regression analysis). Statistical processing was carried

36
out using SPSS 17.0.
2.2. Methods and Stages of Studying the Temporal Characteristics of
Individualism-Collectivism
2.2.1. Justification and Specifics of Applying the Content Analysis Method
The first ethnometric data on I-C in Ukrainians appeared only in the mid-90s, so
in order to study the temporal dynamics of I-C during 1900-2000, another method needs
to be used. The only viable approach seems to be content analysis of printed literature
using a linguistic corpus. Although content analysis is not as precise a method as surveys
using specialized scales, and only allows studying the two main
constructs—individualism and collectivism—without their detailed structure, it is
currently the only method for studying the temporal dynamics of I-C.
The object of content analysis in this case can be both individual words associated
with individualism or collectivism, and pronouns. The latter appears to be a more
promising object, as it does not require prior surveying, and, as shown in the previous
section, some groups of pronouns ("I" and its derivatives, "you" and its derivatives, "we"
and its derivatives) are reliably associated with this cultural syndrome.
Since the Ukrainian language is not part of the Google Books Ngram corpus, and
there is also no national linguistic corpus of the Ukrainian language, the largest interest
for our research lies in the Russian language corpus. The Russian-language corpus in he
Google Books Ngram from 1900-2000 contains 490,855 books, encompassing over 55
billion words.
Throughout the 20th century, bilingualism essentially dominated in Ukraine, with
a more or less pronounced prevalence of the Russian language. In the eastern, northern,
and southern regions, the Russian language distinctly dominated and continues to hold

37
leading positions to this day. For example, as noted by Krypyakevych [13, p. 263], in the
late 1980s, there were only 16 Ukrainian-speaking schools in all regional centers of
eastern, northern, and southern Ukraine. As Boyko writes [1, p. 547], in 1953, there were
1.4 million children studying in Ukrainian schools across Ukraine, and 3.9 million in
Russian and mixed schools.
Regarding book publishing, Ukraine published more Ukrainian books than
Russian ones only for 45 years in the 20th century—from 1925 to 1980. These data refer
only to the total circulation, not unique book titles [118]. The number of unique titles of
Ukrainian books never exceeded those of Russian books [118], and from 1969 to 1980,
the number of Ukrainian journals and books sharply decreased from 60% to 20% [23, p.
447-452].
The situation of formal bilingualism and the de facto dominance of the Russian
language in Ukraine continues even after the dissolution of the USSR. For example, at
present, only 14% of internet pages in Ukraine are in Ukrainian [24], and only 38% of
Ukrainian citizens speak exclusively Ukrainian in everyday life [119].
Therefore, in our opinion, using content analysis of the Russian language is
acceptable for studying individualistic and collectivist orientations in Ukraine during the
20th century. Moreover, such analysis can be used to study the orientations of the entire
Russian-speaking population of the former USSR. However, this conclusion requires
studying the specifics of Russian language usage in each republic of the former USSR,
which is beyond the scope of this study.
Of course, for a complete picture and for comparison with the data on the Russian
language, it will be necessary in the future to study the usage of pronouns in
Ukrainian-language books. Unfortunately, at present, such a study, due to the absence of
a linguistic corpus for the Ukrainian language, is extremely labor-intensive and,
therefore, practically unfeasible.

38
2.2.2. Work with the Google Books Ngram Database
We conducted a search in the Google Books Ngram database for all personal and
possessive pronouns in Russian, both in modern and pre-revolutionary orthography – a
total of 114 words (see Table 2.1). In addition to the groups presented in Table 2.1, we
also studied the frequency of usage of all singular pronouns, all plural pronouns, their
differences, the differences between the first person singular and plural, and pronouns as
a whole, as parts of speech. It should be noted that since the polite form of the second
person singular in Russian ("Вы" and derivatives) is identical to the second person plural,
this group was not used for the analysis of all singular pronouns and all plural pronouns
(but was used for the analysis of second-person pronouns in general).
Table 2.1
Pronouns used in content analysis
Group Pronouns
First person singular я, меня, мне, мной, мною, моя, мое, мои, моего, моему,
моей, моею, моих, моим, моими, моихъ, моимъ, мнъ
First person plural мы, нас, нам, нами, наш, наша, наше, наши, нашего,
нашему, нашим, нашем, нашу, нашей, наших, нашими,
насъ, намъ, нашемъ, нашихъ, нашъ, нашимъ
Second person
singular
ты, тебя, тебе, тобой, тобою, твой, твоя, твое, твои, твоего,
твоему, твоем, твою, твоей, твоею, твоих, твоим, твоими,
тебъ, твоимъ, твоемъ, твоихъ
Second person plural вы, вас, вам, вами, ваш, ваше, вашего, вашему, вашим,
вашем, ваша, вашу, вашей, ваши, ваших, вашими, васъ,
вамъ, вашемъ, вашъ, вамъ, вашимъ, вашихъ
Third person
singular
он, его, него, ему, нему, нем, она, ее, нее, ей, ней, ею, нею,
оно, онъ, ея, немъ
Third person plural они, них, ими, ними, их, оне, ихъ, нихъ
Notes: The pronouns "мой", "мою", "моем" were not used, as they are homonyms for other parts

39
of speech; the pronouns "им", "ним" were used only in the analysis of all pronouns in general, as they
are forms of both the third person singular and third person plural.
The search was conducted using the online interface of Google Books Ngram
Viewer at the following address: https://books.google.com/ngrams. Search parameters:
Years - from 1900 to 2000; Corpus - Russian language, 2012 version; Smoothing - 0;
Case sensitivity - none.
The data obtained were processed using a range of complex statistical methods.
Statistical calculations were performed using SPSS 17.0, unless another program is
specified (see below).
2.2.3. Processing of Content Analysis Data
The result of the search in Google Books Ngram is the frequency of usage of a
given word in a specific year, that is, the percentage of the searched word in relation to
the total number of words. In other words, the number of pronouns in any given year is a
normalized value of the total number of words published in books that year (or more
precisely, present in the Google Books Ngram database for that year). We also tested
other normalization methods – in particular, normalization based on the frequency of the
most common words, used by Acerbi et al. [104]. However, since the results of this
normalization (based on the frequency of the most common Russian words "и" and "на"
[120]) were identical to normalization based on the total number of words, we continued
using only the latter method.
To study changes in the usage of pronouns across different periods of the 20th
century, we used regression analysis data, performed separately for each sub-period.
Before regression analysis, the data were checked for normal distribution, outliers,
multicollinearity, and equality of variances.
To investigate the form of the temporal trend, we used the "curve fitting" test,
comparing linear, cubic, and quadratic trend forms.

40
For examining correlations between time series, we first assessed their stationarity
using the Dickey-Fuller test (the "tseries" package for R software). If the time series did
not show stationarity over the lag interval = 1 year, they were transformed by calculating
the first-order difference (the change in the series between two consecutive years). After
these manipulations, all time series became stationary, allowing us to investigate their
correlations using Pearson's method.
To compare the frequency of usage of different words, we conducted their
standardization. Standardization is not necessary for studying the frequency of pronouns,
as the frequency of various pronoun forms reflects the natural structure of the language,
and interfering with it would distort the results. However, standardization is crucial for
other parts of speech. Specifically, we used standardization to study the frequency of
individualistic and collectivist words derived from the work [96]. Standardization was
performed using formula (2.1):
(2.1)
where x is an individualistic or collectivistic word; fx,t - is the average frequency of word
x for year t; μx- is the average frequency of word x across all years; σх- is the standard
deviation of word x across all years.
To find statistically significant change points in the time series of pronouns, we
used the Change-Point Analyzer [123]. The search was conducted with 1000 bootstrap
replications. The result of the search is a set of change points, the 95% confidence
interval for each point, and its level (its ordinal number).
When using change-point search methods, two important conditions must be met:
the residuals of the time series must demonstrate normal distribution and be independent
(without autocorrelation).
Since there is no consensus on whether time series should be transformed when

41
residuals deviate from a normal distribution, we applied a Box-Cox transformation
(using the algorithm for the R software environment [125]) solely for comparison
purposes.
It is known that autocorrelation presents one of the most serious problems when
working with time series. Autocorrelation means a property of the time series where
each subsequent value can be predicted based on the previous value. In other words, the
data are not independent of each other. Various approaches exist for working with series
exhibiting autocorrelation, and removing autocorrelation is quite a challenging task that
may negatively affect the results. In our opinion, the most optimal strategy for dealing
with autocorrelation was demonstrated in the work [27], where the authors modeled
autocorrelated processes in a given time series to determine the extent to which
autocorrelation distorts the change point search results. We used the same approach.
Modeling autocorrelation in the R software environment was carried out using formula
(2.2):
(2.2)
where , N is the length of the time series (=100), σ² is the standard
deviation, Y is the mean, ρ is the autocorrelation coefficient.
The autocorrelation coefficient can take values of -1, -0.8, -0.5, -0.2, 0, 0.2, 0.5,
0.8, 1. Each time series at each ρ level was used to search for change points; the analysis
was repeated 1000 times. As a result of this approach, it was shown that more than 80%
of the change points at the level -0.2 ≤ ρ ≤ 0.2 coincide with the change points at ρ = 0
(no autocorrelation), which is a favorable indicator [27]. Therefore, it can be concluded
that the impact of autocorrelation on the time series of pronouns we analyzed is
moderate, and thus the results of identifying statistically significant change points are
reliable.

42
2.2.4. Working with the European Social Survey Database
Studying the dynamics of I-C in the 21st century using content analysis of
linguistic corpora is currently not feasible. There are several reasons for this. First, the
period is too short. Second, the Google Books Ngram database includes books published
only up to 2008. Third, in the 21st century, Ukraine is an independent state, making the
use of content analysis in Russian less methodologically justified compared to the 20th
century.
In search of a method to study the dynamics of I-C in the 21st century, we turned
to the data from the European Social Survey (ESS) project. This project involves
surveys conducted every two years among residents of European countries (more than
20 countries). Ukraine participated in the ESS from 2004 to 2012. Although this is a
relatively short period, covering five waves of the survey, it provided a wealth of
material for scientific analysis and interpretation.
Among the various parameters studied in this project, which are primarily relevant
to sociologists and political scientists, we focused on the results of the value orientations
survey conducted using Schwartz's methodology.
Social psychologist Shalom H. Schwartz developed his theory of basic human
values as an extension and complement to the research initiated by Geert Hofstede [88;
90]. The theory identifies ten values, which can be grouped into four higher-order
factors: 1) Openness to change (values of Self-direction and Stimulation); 2)
Self-enhancement (values of Hedonism, Achievement, Power); 3) Conservation (values
of Security, Conformity, Tradition); 4) Self-transcendence (values of Universalism and
Benevolence) [10]. These four groups form two bipolar dimensions: Openness to change
versus Conservation, and Self-enhancement versus Self-transcendence [88].
The first and most popular value scale comprises 57 statements, each rated on an
asymmetric scale from -1 to 7. For the ESS, Schwartz developed the Portrait Value
Questionnaire [122], which includes 21 descriptions of individuals. Respondents

43
evaluate each description on a 6-point scale based on how similar the portrait is to
themselves.
Some researchers have already analyzed the value orientations of Ukrainians
using ESS data. For example, Rudnev and Magun [21] conducted a detailed analysis of
the 2004 survey data and concluded that Ukrainian values display borderline tendencies
compared to other European countries. Shestakovsky [93] briefly addressed the temporal
dynamics of values based on four ESS waves. These studies analyzed values either
according to Schwartz's four-factor model or using a customized factor analysis
somewhat different from Schwartz’s original results.
Meanwhile, the ten values can be grouped not only into a four-factor model but
also into a two-factor higher-level model [91]. One factor represents personal values
(values of power, achievement, hedonism, stimulation, self-direction), and the other
represents collective values (values of benevolence, conformity, tradition). The
remaining two values—universalism and security—contribute almost equally to both
factors. This model is particularly interesting for our purposes, as it closely resembles
I-C models in cross-cultural psychology. Therefore, we decided to examine this model in
detail.
The results of the Ukrainian surveys were downloaded from the ESS website
(http://www.europeansocialsurvey.org). Raw data were centered according to ESS
recommendations [122]. The centering procedure involves correcting for each
respondent's response style (tendency to give similar types of responses). To do this, the
mean of all the respondent's answers is calculated and then subtracted from the score for
each value. Values for each key were obtained according to the ESS guidelines [122],
and the data were grouped into two categories—personal values and collective values.
Statistical processing of the data was standard and included calculating descriptive
statistics (mean, standard deviation, tests for normality of distribution, homogeneity of
variance, and outlier detection), comparing means using Student's t-test, and conducting
Spearman correlation analysis. Statistical analysis was performed using SPSS 17.0.

44
CHAPTER 3
ANALYSIS OF THE RESULTS OF EMPIRICAL RESEARCH
3.1. The "spatial" structure of Individualism-Collectivism in Ukraine
3.1.1. Factor structure
During the survey, 614 individuals submitted their responses from all regions of
Ukraine. Ten responses were excluded (either all answers were uniform, or Ukraine was
not specified as the place of residence). The remaining 604 responses (197 men and 407
women) were used for statistical analysis. Participants’ ages ranged from 18 to 69 years
(M=37.8).
CFA was conducted, yielding indices for models with different numbers of factors
(Table A.1). For comparison, Table A.1 also includes indices from the original English
scale by Singelis et al. and its Spanish adaptation, based on data from published sources.
Additionally, we calculated three indices not present in those
publications—SRMR, CFI, and TLI. For the four-factor model, these were 0.072
(adjusted after the Satorra-Bentler test: 0.070), 0.65 (0.66), and 0.62 (0.64), respectively.
For the one-factor model: 0.092 (0.090), 0.36 (0.37), and 0.32 (0.33). For the two-factor
model: 0.079 (0.077), 0.53 (0.55), and 0.50 (0.51). For the three-factor model (HI and VI
in one factor): 0.077 (0.075), 0.59 (0.61), and 0.56 (0.58). For the three-factor model
(HC and VC in one factor): 0.075 (0.073), 0.59 (0.60), and 0.56 (0.57).
Although CFA provides numerous indices for evaluating model parameters, the
most important index is considered to be SRMR (standardized root mean square
residual). Next, RMSEA (root mean square error of approximation) and CFI
(comparative fit index) are recommended for consideration [87]. For a model to be
deemed statistically acceptable, the indices should meet the following criteria: CFI > 0.9,

45
SRMR < 0.08, RMSEA < 0.06 [53; 54].
In our analysis, the SRMR index was below the required 0.08 threshold for the
two-, three-, and four-factor models, with the best (lowest) result found in the four-factor
model. The RMSEA index achieved optimal values only for the four-factor model. The
CFI index was also highest for the four-factor model, though it did not reach the required
0.9 threshold. However, this index is relative and highly dependent on the χ² value (the
same applies to the relative index TLI, Tucker-Lewis Index).
Other indices are not critical for model evaluation but are included for
completeness and to compare our data with other studies. For example, the χ² value in
similar analyses rarely reaches acceptable (low) levels but serves as a starting point for
calculating other indices. This value was the lowest for the four-factor model (indicating
it is the best model), and our four-factor model even outperformed the four-factor model
of the Spanish scale. The χ²/df index, which should be <0.03 for good models, is more
informative than the χ² value. As shown in Table A.1, this index is also the best for the
four-factor model, with our model again outperforming the Spanish version. The GFI
(goodness of fit index) and AGFI (adjusted goodness of fit index), though rarely used in
modern CFA, also favor the four-factor model.
The correlation between factors in the two-factor model was 0.28. In the
three-factor model (HI and VI in one factor), the correlations were: Individualism-HC
0.25; Individualism-VC 0.21; HC-VC 0.49. In the three-factor model (HC and VC in
one factor): Collectivism-HI -0.007; Collectivism-VI 0.30; VI-HI 0.33. The correlation
values for the four-factor model are presented in Table 3.1. It is noteworthy that the
significant correlation between VC and HC does not make the two- and three-factor
models superior to the four-factor model. Even the three-factor model, where VC and
HC are combined into one factor, is not better than the three-factor model where HI and
VI are combined into one factor.

46
Table 3.1
Correlations Between Factors for the Four-Factor Model
VІ HC VC
HI 0\0.37\0.34 0.2\-0.07\0.07 -0.08\?\-0.19
VІ 0\?\0.25 0.14\0.22\0.25
HC 0.39\0.71\0.49
Note: Results from Singelis et al. [51] \ Gouveia et al. [47] \ results of this study; highest values
are in bold.
The Cronbach's alpha for the VI and HC scales is high, close to or exceeding 0.7.
For the VC scale, this value is 0.64, which is also acceptable since Cronbach’s alpha for
this scale in other studies does not exceed 0.7. The lowest Cronbach’s alpha value was
obtained for the GI scale—0.56. This scale performs poorly in other studies as well, with
the Spanish version of the scale showing a very low value of 0.48 (Table A.1). Given the
high Cronbach’s alpha values for the two-factor model, it can be recommended to
researchers interested in studying only individualism and collectivism without vertical
and horizontal components. However, it is important to note that this model is
statistically inferior to the four-factor model overall.
The factor loadings for each scale item in the four-factor model are shown in
Table 3.2 and Figure 3.1. The data generally align well with the findings of Singelis et al.
[51]. Low loadings for items 25 and 13 are consistent across both studies. Differences
were observed for items 1, 32, 30, 29, and 17 in our study compared to Singelis et al.
Notably, the first four of these items also posed challenges in the Spanish adaptation of
the scale.

47
Table 3.2
Factor Loadings for the Four-Factor Model
HI x1 x5 x6 x15 x18 x21 x25 x32
ps 0.27 0.44 0.37 0.45 0.43 0.42 0.31 0.27
G0.06 0.13 0.12 0.78 0.11 0.45 0.16 0.01
S 0.48 0.30 0.27 0.53 0.49 0.62 0.29 0.46
VІ x4 x8 x10 x12 x19 x23 x26 x30
ps 0.46 0.36 0.51 0.60 0.64 0.53 0.61 0.31
G 0.33 0.66 0.58 0.43 0.29 0.65 0.37 0.11
S 0.45 0.58 0.53 0.46 0.54 0.57 0.52 0.46
HC x2 x9 x11 x14 x16 x20 x22 x28
ps 0.39 0.37 0.45 0.66 0.41 0.45 0.45 0.57
G 0.40 0.33 0.27 0.50 0.43 0.40 0.47 0.44
S 0.48 0.50 0.38 0.67 0.51 0.42 0.44 0.58
VC x3 x7 x13 x17 x24 x27 x29 x31
ps 0.66 0.53 0.29 0.27 0.66 0.40 0.30 0.35
G 0.42 0.13 0.49 0.41 0.49 0.35 0.29 0.46
S 0.60 0.45 0.28 0.45 0.57 0.45 0.40 0.39
Notes: x1–x32 – scale items; S – results from Singelis et al. [51], G – results from Gouveia et al.
[47]; ps – present study; loadings with the smallest values are highlighted in bold.

48
Figure 3.1. Factor structure of the scale
Notes: x1–x32 – item numbers in the scale; VC – vertical collectivism; HC – horizontal
collectivism; VI – vertical individualism; HI – horizontal individualism; numbers between the factors –
correlation coefficients; numbers on the inner edge of the items – factor loadings; numbers on the outer
edge – amount of variance.
The relatively low loading for item 30 is likely due to its reverse-scored nature,
which tends to confuse respondents. For the other items, the low loadings are probably

49
not due to translation issues (as these items are relatively simple to translate) but rather
to cultural nuances that emerge when transferring the scale to a different context. Two of
these items (1 and 32) belong to the HI scale, which has the lowest Cronbach’s alpha
value. Therefore, the only item that appears problematic solely in our study is item 17,
despite it being straightforward to translate.
Attempts to exclude problematic items (individually or collectively) did not
improve model indices. Therefore, the only feasible approach to enhancing the reliability
of the VK and particularly the GI scales might be to replace items 1, 32, 29, and 17
entirely. However, such replacements could lead to deviations from the original English
version's meaning, complicating cross-cultural comparisons of data collected in Ukraine
with those from other countries. As an alternative, researchers could develop a scale
specifically tailored to the Ukrainian context, employing all stages of exploratory
research, including principal component analysis and EFA. However, given the need for
validation in other countries, such a task may not be scientifically justified.
CFA indicates that the four-factor model is the best among models with four or
more factors. However, the question remains whether a stable factor structure exists for
models with more than four factors. To investigate such models, EFA is required, but this
introduces methodological challenges.
In contemporary literature, opinions differ on the relationship and
interchangeability of CFA and EFA. Some authors [63] advise against using both
methods simultaneously, emphasizing the importance of choosing one approach before
starting the research. Others highlight the full interchangeability of CFA and EFA [29].
The most common approach in modern scale development involves using EFA at the
beginning and CFA at the end [31].
Taking into account these and other recommendations for proper EFA application,
it was decided to perform EFA solely to explore the presence of stable models with a
large number of factors. Initial analyses using principal component analysis and Monte
Carlo simulation [124] identified 10 and 7 factors, respectively. However, as shown in

50
the scree plot in Figure 3.2, models with four or more factors lie above the inflection
point; a five-factor model might be theoretically possible; but models with more factors
fall on the flat portion of the graph and are not worth pursuing further.
Figure 3.2. Scree Plot
An EFA with five factors and orthogonal rotation (Varimax method) revealed that
the emergence of an additional scale was due to the splitting of the VI scale. These two
scales include items 4, 8, 10, 23, 30, and 12, 19, 26, respectively. Items 4 and 30 load
almost equally on both scales. Interestingly, none of these items were identified as
problematic in the previously conducted CFA. Moreover, the VI scale shows the highest
Cronbach’s alpha value (0.073) (Table A.1). These results indicate that the five-factor
model cannot be considered satisfactory.
In summary, it can be confidently stated that the four-factor model is the only
statistically stable model of the I-C structure. Notably, a similar model has been
identified in nearly all countries where the Singelis et al. scale has been used. One of the
few exceptions is Italy, where a three-factor model, combining VC and HC into one
factor, was shown to be the best fit [28].
It is also important to emphasize that our study was entirely based on an online

51
survey. Since some of the obtained statistical indicators are higher than those in studies
using traditional survey methods, the results presented here may support the potential of
ethnometric tools in similar research.
Overall, the use of the widely recognized Singelis et al. scale, adapted for use in
Ukraine, helps fill gaps in ethnometric research in the country and expands its
applicability in cross-cultural studies.
3.1.2. Age, gender, and regional characteristics
The average scores and standard deviations for the four I-C factors across the
sample are as follows: HI – 55.33±7.57; VI – 44.15±10.63; HC – 52.1±8.91; VC –
41.81±9.693. As can be seen, individualism slightly outweighs collectivism, while the
horizontal component is significantly higher than the vertical one. This result suggests
that Ukrainians are more inclined toward independence, uniqueness, and authenticity
without recognizing authority or a strict hierarchical structure in society.
These findings align with previous literature, where a slight dominance of
individualism over collectivism in Ukrainians has been noted [92; 98; 99; 103].
Conversely, other studies indicate a minor prevalence of collectivist orientations [20; 75].
These discrepancies likely stem from the specific social and age groups studied,
highlighting the complex structure of this construct among Ukrainians and its
dependence on the social context. The dominance of the horizontal component over the
vertical suggests that Ukrainians lean more toward a European model of societal
organization rather than an American one. Thus, Ukraine’s state-building efforts might
benefit from focusing on the experiences of countries like Sweden, Austria, or
Switzerland rather than the United States.
The values of I-C factors grouped by various independent variables are presented
in Table 3.3.
To explore the influence of different factors on I-C, multiple regression analysis
was conducted. The dependent variables were the four I-C factors: VI, HI, VC, and HC.

52
Independent variables included gender, age, religiosity, language used in daily
communication, and the region of residence. Non-metric variables were coded as 1 and 0
(male – female; Ukrainian – Russian language; Ukrainian-speaking region –
Russian-speaking region). The regression results are presented in Table 3.4.
Their influence on individualism is much smaller: 2% for HI and 4.5% for VI,
with the HI model not being statistically significant.
Gender affects only the collectivism dimensions, explaining 1.7% of the variation
in HC and less than 1% in VC. In both cases, women show higher scores.
The question of whether gender differences exist in cultural orientations remains a
matter of debate. Some researchers emphasize that cultural and gender differences are
incomparable and do not overlap (just as cultural differences cannot be reduced to
individual ones) [37; 71]. Others, however, do demonstrate such differences — for
example, in individualistic Switzerland, an individualistic orientation is more
characteristic of men [68], whereas in collectivist Cameroon, it is more typical of
women [79]. Consensus exists only regarding the notion that individualism,
independence, and autonomy are more characteristic of masculine traits, while a
dependent position is associated with feminine traits, aligning with the values of
collectivism (reviewed in [37]). This conclusion is consistent with our findings: gender
differences in cultural orientations in Ukraine are pronounced and statistically
significant.
Age influences all four I-C factors. The most significant effect is observed in VI,
where age explains 3.5% of the variance in the dependent variable; for the other three
factors, the age effect is minimal (around 1%). Age has an inverse effect on
individualism factors (individualistic orientation is more characteristic of the youth) and
a direct effect on collectivism (increases with age).

53
Table 3.3
Average Values and Standard Deviations for I-C Factors
Independent
Variables HI VІ HC VC
Gender:
men
women
54.62±7.96
55.59±7.42
44.9±10.26
43.87±10.77
49.64±9.45
53.02±8.52
39.45±9.26
42.69±9.72
Language:
Ukrainian
Russian
55.23±7.73
55.55±7.23
44.17±10.49
44.1±10.98
52.2±9.14
51.88±8.39
42.3±9.9
40.72±9.15
Region: А
Ukr.-speaking
Rus.-speaking
55.15±7.59
56.14±7.57
43.96±10.40
45.12±11.79
52.27±8.89
51.19±9.1
42.11±9.89
40.66±8.69
Region: B
Ukr.-speaking.
Rus.-speaking.
55.31±7.52
55.3±8.00
43.92±10.46
45.28±12.08
52.31±8.71
51.42±9.92
41.98±9.87
41.48±8.78
Residents:
urban
rural
55.41±7.58
54.4±7.55
44.14±10.73
44.23±9.64
52.07±8.85
52.45±9.63
41.46±9.71
45.88±8.55
Note: A – the region where the participant has lived for most of their life; B – the region where the
participant currently lives.

54
Table 3.4
Results of Multiple Regression
Vari-
ables df F p R2β t p Partial
R2
HI
age
5; 495 2.025 0.07 0.02
-0.11 -2.36 0.02 0.011
VІ
age
relig.
5; 495
4.629 <0.001 0.045 -0.19
0.10
-4.27
2.23
<0.001
0.03
0.035
0.009
HC
relig.
gender
age
5; 491 9.518 <0.001 0.088
0.21
-0.13
0.1
4.70
-3.01
2.29
<0.001
0.003
0.02
0.041
0.017
0.009
VC
relig.
gender
age
5; 495 13.83 <0.001 0.123
0.29
-0.1
0.08
6.61
-2.26
1.98
<0.001
0.02
0.05
0.077
0.009
0.007
Note: Dependent variables – I-K factors (GI, VI, GC, VC); independent variables – gender, age,
religiosity index, language of daily communication, region of residence; only those independent
variables are presented that show a statistically significant effect on the dependent variables.
When examining the correlation between age and I-C factors separately for men
and women (thus exploring the joint effect of age and gender), an interesting observation
is that statistically significant correlations for individualism factors are only seen in
women (r = -0.11, р=0.04 for HI; r = -0.19, p<0.0001 for VІ), while for collectivism
factors, they appear only in men (r=0.20, р=0.02 для HC; r=0.35, p<0.0001 для VC). In
other words, the collectivist orientation of women does not change with age, but

55
individualistic orientation is more typical of the younger generation. For men, the
reverse is true: individualistic orientation remains constant with age, but collectivist
orientation is more typical of the older generation. It is, however, unclear whether
collectivist orientation truly increases with age or if it is simply a characteristic of older
generations, raised on the ideals of the past (the issue of predominant collectivist
orientation in the USSR will be addressed in the next chapter).
Age-specific aspects of cultural dimensions have received considerable attention
in the literature. Le Bon regarded individualistic culture as a higher form of culture,
evolving from collectivist culture due to the natural inequality of people; the
transformation of cultures from collectivist to individualistic represents a natural
evolutionary process of societal transformation [16]. Hofstede found a correlation
between a country’s financial well-being and the degree of individualism [49], indicating
that this construct may change over time with economic growth, potentially manifesting
in generational differences. Indeed, ethnometric measurements show that younger
generations exhibit more individualistic orientations, while older generations
demonstrate more collectivist tendencies [73]. This pattern has also been observed in
post-Soviet countries [15; 17; 103].
Our sample demonstrates a similar trend. Although the participants’ ages ranged
from 18 to 69 years, it is worth noting that the average age of respondents was only 37.8
years. Additionally, the survey was conducted online, a medium not widely used by
older individuals. There is little doubt that employing traditional paper-based survey
methods and including more elderly participants would highlight age-related differences
even more distinctly.
The religiosity index has a minor impact on individualism (less than 1% for VI)
but a significant one on collectivism (4.1% and 7.7% for HC and VC, respectively). The
influence is direct, meaning high religiosity scores correspond to high scores on these
scales.

56
When examining the correlation between religiosity and I-C factors separately for
men and women (thus exploring the joint influence of religiosity and gender), a
statistically significant correlation for individualism is observed only in women
(r=0.13, p=0.02 for VІ; not significant for HІ). For collectivism, both genders show
statistically significant correlations: r=0.29, p=0.001 (HC in men), 0.19, p<0.0001 (HC
in women), 0.32, p<0.0001 (VC in men), 0.30, p<0.0001 (VC in women). Correlation
coefficients for men and women do not show statistical differences at α=0.05. Thus, it
can be concluded that there is no joint influence of gender and religiosity (at least in the
case of collectivism).
To study regional differences in survey responses, we divided participants into
two groups: a Western region (Khmelnytsk, Ivano-Frankivsk, Zhytomyr, Volyn, Lviv,
Ternopil, Rivne, Vinnytsia, Cherkasy, Kyiv, Zakarpattia, Poltava, Sumy, Chernivtsi,
Chernihiv, Kirovohrad oblasts) and an Eastern region (Mykolaiv, Dnipropetrovsk,
Zaporizhzhia, Kharkiv, Luhansk, Donetsk, Odesa, Kherson regions, and Crimea). This
division is justified, as these regions demonstrate differences in political orientation
toward pro-Ukrainian or pro-Russian candidates during elections (e.g., the 2004 and
2010 Presidential elections [121]) and in the predominant use of Ukrainian or Russian in
daily communication [117].
Regarding language of daily communication, given the insufficient number of
participants who indicated exclusive use of Russian (N=11), we decided to form only
two groups: Ukrainian (participants who use exclusively or predominantly Ukrainian)
and Russian (those who use exclusively or predominantly Russian).
Results of the multiple regression analysis indicate that neither the language of
daily communication nor the region of residence has a statistically significant effect on
I-C factors (hence, working hypothesis #3 was not confirmed). It should be noted that
the issue of regional differences has not been thoroughly explored in cross-cultural
psychology. Studies in this area are still scarce, but this can be easily explained. The
ethnometric approach is meaningful primarily for large, ethnically, and culturally

57
heterogeneous countries like the USA [114], Brazil [33], or Russia [15]. Historical and
contemporary realities suggest that Ukraine is a mentally heterogeneous country. At a
minimum, two regions in Ukraine could be expected to show differences using
ethnometric approaches: the eastern, predominantly Russian-speaking region, and the
western, predominantly Ukrainian-speaking region.
From the literature, two positive results indicate this "mental heterogeneity" [26;
60], and one negative result found no differences between western and eastern Ukraine
[20]. As for the reason this hypothesis was not confirmed in our study, we attribute it to
the insufficient number of respondents from the eastern regions (only 71 participants
indicated this region as their current residence, and 88 as the region where they had lived
most of their lives). Respondent activity from eastern regions was significantly lower
than from western regions, highlighting the need for further efforts to distribute the
survey among eastern Ukrainian respondents.
The distinction between urban and rural residents did not receive a statistical
interpretation in this study due to the small representation of rural residents in the
sample (only 40 participants). Overall, as seen in Table 3.3, the VC scale scores are
higher among rural residents (45.88 vs. 41.46), which may indicate the expected
predominance of collectivism over individualism in these participants.
3.1.3. The Structure of Collectivism at the Level of In-Groups
To investigate the strength of ties with various in-groups, which, according to
Triandis, characterizes the degree of collectivist orientation [106], we conducted a
correlation analysis between the scores participants obtained from questions 36–39 of
the scale and their scores on the four I-C factors. We selected several key in-groups
representing the closest environment of each individual—immediate family, other
relatives, etc. (see questions 36–39 of the scale). According to Triandis, these groups
exert the greatest influence on individuals, especially in collectivist societies.
The average scores across the entire sample were as follows: ties with family:

58
7.76±1.75; ties with relatives: 5.67±2.44; ties with friends: 6.07±2.04; ties with other
people: 4.85±2.06. As expected, the strongest ties are with the immediate family, while
ties with friends are slightly stronger than those with more distant relatives.
Also as expected, the strength of ties with these in-groups shows a well-defined
statistically significant correlation with collectivism factors (Table 3.5), while for
individualism factors, there is only a weak negative correlation between HI and ties with
family. The only exception is the absence of correlation between ties with friends and
VK, which can be explained by the nature of VK, representing a preference for
hierarchical relationships, whereas friendship implies equality. Similar results were
obtained by researchers studying the structure of collectivism in Spain [47].
In addition to providing information about the structure of collectivism in Ukraine,
these data serve as further validation of the Ukrainian-language scale, as they imply that
the scales are indeed measuring the intended construct.
According to the model by A. Realo and J. Allik, connection to society in the form of
patriotic feelings is one form of collectivism [81]. We aimed to test this hypothesis by
including four additional questions in the scale to establish a link between I-C and
nationalism (questions 34 and 35) and I-C and patriotism (questions 40 and 41).
Given that patriotism and nationalism are two related forms of national
self-identification [65], it is reasonable to consider this indicator as the sum of scores for
all four questions. This indicator ("national self-identification scale") shows a
statistically significant correlation with the language of communication (r=0.12;
p=0.009), being higher among those who consistently or predominantly use Ukrainian
(M=22.19) than among those who consistently or predominantly use Russian (M=20.65).
This correlation with the language of communication can be seen as further validation of
the national self-identification scale.

59
Table 3.5
Pearson Correlation Between I-C Factors
and the Strength of Ties With Various Groups
Groups HІ VІ HC VC
Family -0.11; p=0.01* 0.01; p=0.81 0.36; p<0.001* 0.34; p<0.001*
Relatives -0.03; p=0.53 0.02; p=0.63 0.35; p<0.001* 0.29; p<0.001*
Friends 0.03; p=0.51 0.02; p=0.72 0.37; p<0.001* 0.06; p=0.15
Others -0.07; p=0.14 0.11; p=0.01* 0.49; p<0.001* 0.30; p<0.001*
Nation 0.09; p=0.05* 0.11; p=0.02* 0.33; p<0.001* 0.35; p<0.001*
Note: Family: Strength of ties with immediate family (children, spouse, parents); Relatives:
Strength of ties with more distant relatives (grandparents, aunts, uncles, etc.); Others: Strength of ties
with people surrounding the participant in daily life (colleagues, community members, neighbors, etc.);
Nation: Sum of scores from questions 34 and 35 (nationalism scale) and questions 40 and 41
(patriotism scale); Statistically significant correlations at α=0.05 are marked with an asterisk.
The data in Table 3.5 show that national self-identification correlates with all I-C
factors, but the correlation with individualism factors is negligible and barely reaches
statistical significance, while the correlation with collectivism factors is strongly
pronounced. Can the obtained data be considered confirmation of the hypothesis by A.
Realo and J. Allik? In our opinion—no.
Since collectivism reflects a preference for group goals over personal ones, such a
broad interpretation of collectivism essentially implies that a person may sacrifice
personal values for the interests of any group size. In this sense, not only patriotism but
also, for example, religiosity, could be viewed as an expression of collectivism. Indeed,
religiosity can be seen as belonging to a specific social group—a community of people
united by certain goals and values. As already noted, religiosity significantly correlates

60
with collectivism indicators rather than individualism (see Table 3.4); a few empirical
studies by other authors also confirm this conclusion [35].
Of course, history provides numerous examples of individuals sacrificing not only
their interests but also their lives for the benefit of their country or religious group.
However, in our opinion, such an understanding of collectivism is unjustifiably broad. In
cases of self-sacrifice, personality traits come to the forefront, which may have no direct
relation to cultural syndromes.
The traditional understanding of collectivism as the strength of ties with groups
directly surrounding a person (family, colleagues, relatives, friends) most accurately
conveys the essence of this cultural syndrome. These groups are the closest and most
important for each individual, and it is with them that one has the strongest ties.
Collectivist orientation, in turn, may serve as a basis for connections with larger groups
(nation, religious community, humanity), but this does not mean it must include such
connections or explain them. The reverse relationship is also possible: for example, since
religion promotes group integration and establishes behavioral norms, an individual's
religiosity may enhance their collectivist orientation [107].
As some researchers note [43; 78; 72], even such a traditional understanding of
the I-C syndrome as connections with the closest groups is overly broad and should be
reconsidered.
3.2. The Temporal Structure of Individualism-Collectivism in Ukraine
3.2.1. Dynamics of Changes in Individualism-Collectivism During the 20th
Century
The relative frequency of pronoun usage across different groups during the 20th
century is presented in Fig. 3.3. Table 3.6 shows the changes in pronoun usage across
historical periods of the 20th century. The following distinct and well-documented

61
periods were analyzed: 1) Pre-Bolshevik Revolution period (1900–1917); 2) The period
of building a communist society (1918–1991); 3) Pre-Soviet-German War period
(1918-1940); 4) Soviet-German War (1941-1945); 5) Pre-Thaw period (1946-1953); 6)
Thaw (1954-1964); 6) Stagnation (1965-1985); 7) Perestroika (1986-1991); 8)
Post-Soviet Union collapse period (1992-2000); 9) Period from Twenge et al. [110; 111]
(1960–2000) for comparing our findings with their results for the English language.
As shown in Table 3.6, pronoun usage decreased across all groups during the 20th
century, except for third-person singular pronouns. However, this extended period was
characterized by significant fluctuations in pronoun usage. According to the curve
estimation test, none of the trends were linear; instead, the best-fitting statistical model
was a cubic trend (growth–decline–growth), explaining 61% (second-person pronouns)
to 80% (first-person singular pronouns) of the variance. For third-person plural pronouns,
cubic and quadratic trends were nearly identical, explaining only a small percentage of
the variance.
Since the connection between third-person pronouns and I-C is poorly understood,
the subsequent stages of the analysis focused primarily on first- and second-person
pronouns, which are more directly associated with this cultural syndrome. Special
attention was also given to the difference in usage between first-person singular and
plural pronouns, as in our opinion, this difference is a particularly clear indicator of
individualistic or collectivistic tendencies. An upward trend in this difference reflects
growing individualistic orientation and vice versa.
From Fig. 3.3 and Table 3.6, it is evident that first- and second-person pronouns
showed a positive trend from the early 20th century until the Bolshevik Revolution of
1917, as well as from the mid-Stagnation period (around the mid-1970s) to the end of
the 20th century. Since the increase during these periods is observed in both singular and
plural forms, the difference between first-person singular and plural pronouns indicates
that the usage of the former significantly outpaced the latter, providing clear evidence of
a predominant individualistic orientation.

62
Fig. 3.3. Temporal changes in the usage of different pronoun groups during the
20th century.
A notable rise in individualistic orientation is also observed at the onset of the
Soviet-German War. The effects of this rise can be traced through the

63
early-to-mid-1950s. This increase was likely linked to a greater emphasis in printed
publications on the "I," the individual, and internal human resources necessary for
achieving the victory.
The period from 1960 to 2000 is characterized by an increase in all pronoun
groups. In English, during this period, only first-person singular and second-person
pronouns increased in usage, while other pronoun groups decreased [111]. Results for
the Russian language indicate a growing individualistic orientation from 1960 onward,
though the changes are less pronounced than for the English language. To clarify this
observation, we calculated the difference in relative frequency between first-person
singular and plural pronouns and determined its percentage change over the period. For
American English, the increase was 111%, whereas for Russian, it was 4021% (figures
derived from regression analysis).
A distinct decline in individualistic orientation is observed after the Bolshevik
Revolution and before the start of the Soviet-German War, as well as from the
mid-1950s to the mid-1970s. It is unclear to what extent these declines reflect a
quantitative dominance of collectivism over individualism.
During these periods, there may simply have been a relatively low level of
individualism compared to other periods, and collectivist orientation may never have
truly dominated in Ukraine or the USSR to the extent it does in genuinely collectivist
Eastern societies.
If based solely on the quantitative predominance of first-person plural pronouns
over first-person singular ones, such (very slight) predominance occurred only from
1932 to 1938, in 1941, and from 1960 to 1962. Only these short periods can be
considered as having relatively high collectivist orientation compared to other periods.

64
Table 3.6
Statistical Characteristics of Pronoun Usage Across Periods of the 20th Century
Periods
Pronouns
1st person
singular
1st person
plural
1st pers.sin.
minus 1st
pers.plural
2nd person 3rd person
% Sp. % Sp. % Sp. % Sp. % Sp.
All -42.8 -0.61 -40.8 -0.53 -50.8 -0.14 -45.4 -0.59 -35.5 -0.69
Communism -43.7 -0.61 -49.3 -0.87 -0.20 0.25 -38.7 -0.56 -30.4 -0.67
Pre-Revol. 19.2 0.57 2.20 0.22 67.5 0.67 9.50 0.33 -0.9 -0.06
Pre-War -50.6 -0.84 -30.0 -0.90 -118.4 -0.60 -48.0 -0.68 -31.3 -0.71
War 12.0 0.60 -18.4 -0.90 2009 0.90 7.0 0.30 0.9 0.20
Pre-Thaw -4.0 -0.17 -12.7 -0.57 84.3 0.45 3.5 0.17 -10.6 -0.64
Thaw -24.1 -0.66 -12.4 -0.87 -85.6 -0.51 -34.1 -0.77 -15.2 -0.71
Stagnation 16.0 0.59 -7.9 -0.56 398.2 0.84 16.1 0.61 5.9 0.44
Perestroika 16.4 0.37 12.2 0.60 28.6 0.37 4.6 0.37 2.1 -0.03
Post-USSR -5.5 -0.57 -1.9 -0.32 -12.5 -0.28 -14.2 -0.57 -2.7 -0.42
1960-2000 82.4 0.87 17.8 0.47 4020 0.93 59.3 0.86 29.2 0.82
Periods
Pronouns
3rd person
plural all singular all plural
all singular
minus all
plural
all
% Sp. % Sp. % Sp. % Sp. % Sp.
All 10.7 0.30 -36.3 -0.64 -18.3 -0.55 -50.8 -0.53 -32.7 -0.69

65
Notes: % - change in usage percentage (data from regression analysis); Sp. - Spearman's
correlation with year; statistically insignificant correlations at α ≥ 0.05 are italicized; positive numbers,
indicating growth, are in bold; see text for details of periods.
Triandis [107] describes Soviet society as collectivist. Other authors [92], as noted
earlier, emphasize the absence of an equivalent to the English term "privacy" in East
Slavic languages, which also characterizes East Slavic cultures as collectivist. Утім, ці
висновки є лише феноменологічними узагальненнями. However, these conclusions
are merely phenomenological generalizations. Only by examining the correlation
between I-C scores from surveys and the frequency of pronoun usage characteristic of a
society at the time of the survey can we extrapolate these data to the entire 20th century
and more thoroughly address the question of the society's orientation.
An analysis of correlations between the usage of various pronoun groups during
the 20th century (Table 3.7) shows moderate to strong correlations among groups. This
result is not surprising, as all pronouns form a single logical system that constitutes the
linguistic framework. The distinct behavior of third-person singular pronouns, which
differ from other groups in their temporal dynamics profile (Fig. 3.3), is noteworthy.

66
Contrary to expectations, the correlation between first-person singular and plural
pronouns, which are most strongly associated with I-C, is positive, weak, and on the
threshold of statistical significance (r = 0.20; P = 0.05). The correlation between
first-person plural and second-person pronouns is slightly stronger (0.41) but also
positive.
The correlation between groups associated with individualistic orientation
(first-person singular and second-person pronouns) is predictably very strong (0.84).
The positive correlation between pronouns representing individualism and
collectivism raises questions about the independence of these constructs. If
individualism and collectivism were polar opposites of a single construct (as per
Hofstede's model), a negative correlation would be expected. This question is both
intriguing and important, and we will return to it later.
In Figure 3.3, at least three peak periods can be observed—around 1920, 1941,
and 1986. These periods are more pronounced for first-person singular and plural
pronouns and slightly shifted for second-person pronouns. An important methodological
question arises: to what extent are these periods genuine increases in pronoun frequency
rather than mere "white noise"? Additionally, is there a statistical method to assess the
magnitude and significance of temporal changes?
Such a method does exist. The so-called change point analysis is a relatively new
statistical tool developed within the framework of time series analysis. The study of time
series, in turn, is a complex and infrequently used statistical methodology, first
introduced in the mid-20th century. Initially, time series analysis was primarily used in
economics, but with the advent of change point analysis, this branch of statistics has
gained attention from climatologists, medical researchers, and bioinformatics specialists
[61]. As for the application of change point analysis in linguistic studies, we are aware of
only one work where this method has been successfully applied [101]. We aimed to fill
this gap by using change point analysis to study the frequency of pronoun usage. This
method allowed for a deeper exploration of the patterns of pronoun frequency changes in

67
the 20th century.
As shown in Figures 3.4 and 3.5, the statistically significant change points align
quite well with major historical events in Ukrainian and Soviet history of the 20th
century. These include the post-Bolshevik Revolution period in the early 1920s, the
period of the Soviet-German War, and the beginning of Perestroika. Quantitative
characteristics of the identified change points are also provided in Tables 3.8–3.11.
Table 3.7
Pearson Correlation Between the Frequency of Different Pronoun Groups
1st person
plural
1st person
singular
minus 1st
person
plural
2nd
person
3rd person
singular
3rd person
plural
All
singular
All
plural
1st person
singular
0.20*;
p=0.05
0.84*;
p<0.001
0.61*;
p<0.001
-0.30*;
p=0.003
-0.09;
p=0.4
1st person
plural
0.41*;
p<0.001
0.51*;
p<0.001
0.58*;
p<0.001
0.41*;
p<0.001
2nd
person
0.64*;
p<0.001
0.68*;
p<0.001
0.05;
p=0.64
3rd person
singular
0.38*;
p<0.001
0.32*;
p=0.001
0.53*;
p<0.001
3rd peron
plural
-0.55*;
<0.001
0.04;
p=0.71
All
singular
0.23*;
p=0.02
Notes: All time series are stationary over a lag of 1 year; statistically significant results (at α ≤
0.05) are marked with an asterisk.

68
It is noteworthy that the Stagnation period is the longest stretch of the 20th
century without statistically significant change points, justifying its name. This
stagnation appears to have affected not only the economy but also the spiritual and
cultural life of society.
It is also noteworthy that significant changes began in the late period of Stagnation,
during the second half of the 1970s. A considerable number of statistically significant
change points emerge, indicating an increase in the frequency of all groups of pronouns.
In terms of individualistic-collectivistic orientation, as previously noted, this signifies a
strong shift toward individualism (the increase in the usage of first-person singular
pronouns is substantially greater than that of first-person plural pronouns). It is well
known that the end of the Stagnation period was marked by a certain weakening of
central authority in the USSR, which was associated with the advanced age of the senior
leadership of the Communist Party. The early 1980s, commonly referred to as the era of
the “Kremlin elders,” was met with ironic and even negative reactions from society,
which had begun to demand radical change.
A particularly intriguing fact is that the Perestroika period appears on the change
charts as a natural continuation of these transformations, a steady movement toward
self-assertion and independence—the cornerstone values of individualism. This suggests
that the mechanism for the Soviet system's collapse was set in motion even before
Perestroika began; the groundwork for both Perestroika and the USSR's subsequent
dissolution was laid during these profound cultural transformations, which started in the
second half of the 1970s. This conclusion warrants detailed future study.
The data on pronoun usage is both intriguing and important to compare with the
dynamics of Russian individualistic and collectivist word usage. This comparison will
help determine the relevance of using pronouns to study I-C and provide material for
comparative analysis regarding change points and periodic patterns.

69
А
B
C
D
Fig. 3.4. Statistically Significant Change Points in Pronoun Usage (A - difference
between 1st-person singular and 1st-person plural; B - 1st-person singular; C -
1st-person plural; D - 2nd-person)

70
Fig. 3.5. Statistically Significant Change Points in Pronoun Usage and
Individualistic vs. Collectivist Words Over 20th-Century Periods
Notes: Black dots indicate declines; white dots indicate increases; BR - Bolshevik Revolution;
SGW - Soviet-German War; Thaw - Khrushchev Thaw; Stag - Stagnation; Per - Perestroika.
Table 3.8
Statistically Significant Change Points in the Difference Between First-Person
Singular and First-Person Plural Pronouns
Change Point
Confidence
Interval
(95%)
% Change Level
Start
End
19
23
191
5
192
5
-56
1
1930
1924
1931
-95
6
1943
1942
1946
1723
5
1956
1948
1957
-57
8
1977
1973
1977
122
3
1982
1982
1989
59
4
1992
1990
1992
63
2
1994 1993 1995 -17 4

71
Table 3.9
Statistically Significant Change Points in First-Person Singular Pronoun Usage
Change Point
Confidence
Interval
(95%)
% Change Level
Start
End
1923
1909
1925
-17
4
1931
1929
1932
-23
1
1941
1940
1941
30
4
1946
1946
1949
-17
5
1957
1957
1957
-25
3
1979
1977
1979
16
4
1988 1988 1989 29 2
Table 3.10
Statistically Significant Change Points in First-Person Plural Pronoun Usage
Change Point
Confidence
Interval
(95%)
% Change Level
Початок
Кінець
1918
1917
1918
26
3
1923
1923
1924
-20
4
1941
1933
1943
9
2
1945
1945
1945
-15
5
1952
1951
1952
-15
5
1958
1958
1958
-9
3
1967
1965
1969
-3
5
1973
1973
1973
-7
7
1984
1984
1984
7
6
1988 1988 1989 13 5

72
Table 3.11
Statistically Significant Change Points in Second-Person Pronoun Usage
Change Point
Confidence
Interval
(95%)
% Change Level
Start
End
1910
1904
1913
12
2
1923
1923
1924
-30
1
1928
1924
1929
-15
4
1941
1941
1946
23
3
1958
1958
1958
-33
2
1979
1977
1983
22
6
1992
1991
1992
32
5
1994 1994 1994 -14 6
In 2016, Skrebyte et al. [96] published a study examining the use of individualistic
and collectivist words in the Russian subcorpus of Google Books Ngram. The words
were selected through a survey conducted among a sample (N=56) of the
Russian-speaking population in Lithuania. Unfortunately, the authors made significant
methodological errors in processing their results.
First, their data show a pronounced increase in 1918, indicating that they only
included words with modern spelling, ignoring pre-revolutionary orthography. Second,
they standardized only the sum of word usage frequencies, whereas it is necessary to
standardize the frequency of each word individually before calculating the sum.
Otherwise, more frequently used words (e.g., "вместе") will completely overshadow
words with lower frequencies (e.g., "альтруизм"), significantly distorting the final result.
Third, they calculated Spearman's correlation coefficient between two non-stationary
time series, which is entirely unacceptable (see, for example, [64]). Before analyzing the
correlation, time series must be tested for stationarity and made stationary using methods
such as first differencing.
We attempted to correct these errors and conducted a complete reanalysis of the

73
authors' data.
As seen in Fig. 3.6, the profile of changes in the use of individualistic words
closely resembles the profile of first-person singular pronoun usage, differing
substantially from the profile presented in the original study. The usage profiles of
collectivist words and the difference between individualistic and collectivist words
generally show similar patterns (a decline after the Bolshevik Revolution, fluctuations
during the Soviet-German War, and a rise in the 1980s), though these patterns are less
pronounced.
The "curve estimation" method, similar to the case with pronouns, indicates that
the most statistically significant trend is a cubic trend for individualistic words and the
difference between individualistic and collectivist words, while collectivist words
exhibit no clear trend.
The statistically significant change points also share many similarities with the
pronoun usage data (Tables 3.12–3.14). For individualistic words, these include a
decline in the mid-1920s, a rise in the mid-1970s, and another rise at the start of
Perestroika. For collectivist words, there is an increase during the Soviet-German War.
The Pearson correlation between the usage of individualistic words and different
groups of pronouns is significant only for pronouns clearly associated with I-C: 0.22
(p=0.03) for the first-person singular, 0.21 (p=0.03) for the first-person plural, and 0.32
(p=0.001) for the second person. No correlation is observed between the usage of
collectivist words and pronouns. A statistically significant correlation between
individualistic and collectivist words is also absent (r = 0.07; p = 0.46).

74
Fig.3.6. Statistically significant change points in the usage of individualistic and
collectivist words throughout the 20th century.
Notes: From top to bottom: individualistic words, collectivist words, and the arithmetic
difference between them; all words are sourced from [96].

75
Table 3.12
Statistically significant change points in the usage of individualistic words
Change Point
Confidence
Interval
(95%)
% Change Level
Початок
Кінець
190
4
190
3
19
17
115
4
19
18
19
17
19
18
3098
3
19
25
19
25
19
25
-129
4
19
45
19
34
19
46
100
5
19
50
19
50
19
50
-31412
4
19
61
19
53
19
63
33
5
19
76
19
73
19
77
38
3
19
86
19
86
19
86
96
4
19
89
19
89
19
89
9178
1
1996 1994 1996 49 2
Table 3.13
Statistically significant change points in the usage of collectivist words
Change Point
Confidence
Interval
(95%)
% Change Level
Start
End
190
5
190
4
190
5
118
5
190
9
190
9
19
13
-738
4
19
19
19
19
19
41
27
3
19
42
19
41
19
42
830
2
1943 1943 1943 -92 3
Table 3.14
Statistically significant change points in the usage of the difference between
individualistic and collectivist words
Change Point
Confidence
Interval
(95%)
% Change Level
Start
End
19
42
19
42
19
42
-876
2
19
43
19
43
19
43
78
6
19
65
19
49
19
70
45
5
19
89
19
89
19
89
370
3
1995 1991 1995 -34 6

76
We also compared data on the Russian language with data on American English.
Pronouns were taken from the publication [111], individualistic and collectivistic words
from [110], and statistical analysis was conducted as described in section 2.2.3.
A weak positive correlation was found between individualistic and collectivistic
words in English, on the verge of statistical significance (r = 0.21; P = 0.04) (this
correlation is absent in Russian). The correlation between the first-person singular and
first-person plural pronouns in English was slightly higher than in Russian, and also
positive (r = 0.57; P < 0.0001). Along with the results from the correlation between
factors in the factor analysis, similar findings suggest that individualism and
collectivism are two independent constructs. This conclusion contradicts G. Hofstede's
model and supports H. Triandis's model.
Finally, it is worth noting that using such a comprehensive set of pronouns allows
for a fairly accurate estimation of the percentage of pronouns in the Russian language.
The figure is 2.7% (from 2% in 1976 to 3.7% in 1922). This lower than in English,
Italian, German, and French, but higher than in Hebrew, as estimated by Uz [113].
However, our data concerns only personal and possessive pronouns, while Uz, for
estimating the percentage of pronouns in other languages, used automatic (and
presumably imprecise) part-of-speech identification available in Google Books Ngram
(which is not available for Russian). This conclusion about the percentage of pronouns
in different languages has not only purely linguistic significance. For example, Japanese
researchers [58; 59] concluded that languages in which the omission of pronouns is
allowed (e.g., omitting "I" at the beginning of a sentence) belong to collectivist cultures,
and conversely, languages with fixed pronoun usage indicate individualism. Obviously,
languages in which pronouns can be omitted (including Russian) should have a lower
percentage of pronouns than languages with fixed pronoun usage.
The twentieth century is an extraordinarily interesting and dramatic period in
Ukrainian and Soviet history, encompassing such historical events as the Bolshevik

77
Revolution, Civil War, Holodomor, the Soviet-German War, Perestroika, and the
collapse of the USSR. Studying linguistic changes during this period, especially those
associated with cultural values, helps to better understand how personal and cultural
orientations change under the influence of major social upheavals. As our study shows,
the "construction of communism" period (1918-1991) was characterized by a reduced
individualistic orientation compared to the preceding and subsequent periods.
Interestingly, gradual changes symmetrically span the beginning of this period (a strong
decline in individualism begins in the mid-1920s) and its end (a strong increase in
individualism begins in the mid-1970s). During this period, a short spike in
individualistic orientation occurred during the Soviet-German War.
The second important conclusion from the analysis is that the dynamics of
pronoun usage can be considered a sensitive mechanism for society's response to
significant historical events. A reverse relationship may also occur: changes in pronoun
usage in the absence of any noticeable societal shifts may indicate the onset of profound
underlying processes, which, in turn, can lead to radical social transformations. In our
view, such mechanisms were at work in the ideological and value changes that began in
the second half of the 1970s and ultimately culminated in Perestroika and the collapse of
the Soviet Union. Evidence supporting this interpretation includes the sharp increase in
the frequency of pronouns associated with individualistic orientations, against the
backdrop of economic and intellectual stagnation during the late 1970s.
3.2.2. Dynamics of changes in Individualism-Collectivism in the 21st century
The total sample size across five waves of the European Social Survey (ESS) in
Ukraine was 9987 respondents (2004 - 2031, 2006 - 2002, 2008 - 1845, 2010 - 1931,
2012 - 2178 respondents).
Centered values for each of Schwartz’s 10 values during the studied period are

78
shown in Figure 3.7. As seen, the graphs demonstrate a sharp difference between
collective values and individual values. The former have positive values, and the latter
have negative values (i.e., according to the centering procedure, they are lower than the
average value of all responses from each respondent).
The difference becomes even clearer when the values are grouped into two factors
(Figure 3.8). This procedure clearly shows that personal values exhibit a tendency to
increase over the study period, while collective values exhibit the opposite, a tendency to
decrease.
The statistical interpretation of these changes, due to the fact that we have only
five variables, is somewhat limited. For example, the correlation with the year using
Spearman's method is statistically significant (ρ=0.9, p=0.04 for both types of values),
but it is not a reliable method due to the small amount of data. Therefore, we conducted
a Student's t-test between the most extreme values (for both types of values, these are the
years 2004 and 2012), yielding the following results: personal values - t=9.34, p<0.0001;
collective values - t=7.06, p<0.0001. Such a result leaves no doubt that the changes
observed over the study period are statistically significant.
In a recent 2017 publication [85], Santos and colleagues, based on a study of 77
countries, found "a global increase in individualism" over the past half-century.
According to their data, only five countries demonstrate a decline in individualistic
orientations over the studied period. Ukraine is one of these countries. Interestingly, the
authors based their conclusions on the ESS data.
Unfortunately, due to the lack of details on the analysis, it is unclear how they
came to this conclusion. It is possible that they analyzed the ten values in the form of a
symmetrical two-factor model - five values in the individualism and collectivism factors
(a similar approach was also used by other researchers). However, as already noted, this
type of analysis is erroneous because two factors (universalism and security) equally
load both scales and should therefore be excluded from the analysis [91]. As shown by
our analysis using the approach described in section 2.2.4, the ESS data demonstrate the

79
opposite result - a clear and statistically significant trend towards the growth of personal
values and the decrease of collective values. This conclusion is entirely expected and
logically complements our data on the temporal dynamics of I-C over the past century.
Fig. 3.7. Dynamics of changes in Schwartz's 10 values during 2004-2012.
Notes: Бе - Security, Ko - Conformity, Тр - Tradition, Дз - Benevolence, Ун - Universalism, См -
Self-Direction, Ст - Stimulation, Ге - Hedonism, До - Achievement, Вл - Power.

80
Fig. 3.8. Changes in Schwartz's values, grouped into two factors, 2004-2012
Finally, it should be noted that the predominance of collective values over
personal values does not necessarily mean that collectivism dominates over
individualism in Ukraine, as Schwartz’s value model is not identical to Hofstede’s or
Triandis’s cross-cultural models. Furthermore, Schwartz’s ten values are individual-level
values, not cultural ones; they are not values at the country level and do not correspond
to or reduce to cultural syndromes (though they correlate with them) [89].
Nonetheless, the Schwartz model is one of the few tools that allow bridging the
gap between individual and cultural levels of measurement [42], because Schwartz’s ten
values, when compared cross-culturally across countries, group into a new seven-factor
structure [89]. In this regard, as some researchers argue [57; 100], Schwartz's values are
more comprehensive constructs than Hofstede's cultural values, and therefore it is very
useful to consider these two models as complementary.

81
CONCLUSIONS
1. Three approaches were used to study the structure of the cultural syndrome
"individualism-collectivism" in Ukraine: the "spatial" structure (factor structure, age,
gender, regional characteristics, structure at the in-group level, connection with
individual religiosity) was studied using the Singelis et al. (1995) scale; the temporal
structure (dynamics of individualism-collectivism components over time, starting from
1900) was studied using content analysis and Schwartz’s value scale.
2. For the first time, a Ukrainian-language adaptation of the ethnometric tool - the
popular Singelis et al. (1995) scale - was conducted. The adaptation included translating
the scale into Ukrainian using back-translation, as well as studying its validity and
reliability. Construct validity of the translated scale, assessed using factor analysis,
showed that a four-factor model of individualism-collectivism, including vertical and
horizontal components, is statistically the best. Reliability analysis using Cronbach’s
alpha revealed satisfactory reliability for all four scales.
3. It was shown that currently in Ukraine, individualistic orientation slightly
prevails over collectivist orientation, and the horizontal component is significantly
higher than the vertical component. This result suggests that Ukrainians are more
inclined towards independence, uniqueness, and authenticity without acknowledging
authority or a clear hierarchical societal structure. This may indicate that Ukrainians are
closer to the European model of societal organization than the American model, which is
characterized by a strongly expressed vertical component.
4. It was shown that gender influences only the collectivism factors (women have
higher values). Age influences all four factors of individualism-collectivism. This
influence is reverse for individualism (individualistic orientation is more characteristic
of youth) and direct for collectivism (it increases with age). There is a joint influence of
age and gender: when examining the correlation of age with the factors of

82
individualism-collectivism separately for men and women, statistically significant
correlations for individualism factors are observed only for women, while for
collectivism factors, they are seen only for men ((i.e., with age, women's collectivist
orientation remains unchanged, but their individualistic orientation is more characteristic
of youth; men's individualistic orientation does not change with age, but their collectivist
orientation is more characteristic of the older generation). It was shown that neither the
language of everyday communication nor the region of residence has a statistically
significant influence on the individualism-collectivism factors.
5. It was shown that the religiosity of a participant has a minor influence on
individualism but a significant one on collectivism (in both cases, the influence is
directly proportional). The strength of the connection with the studied in-groups
(immediate family, more distant relatives, people surrounding the respondent in
everyday life) showed a well-expressed statistically significant correlation only with the
collectivism factors. It was shown that the "national self-identification scale" correlates
with all individualism-collectivism factors, but the correlation with individualism factors
is minor and on the verge of statistical significance, while the correlation with
collectivism factors is distinctly expressed.
6. One of the first attempts was made to investigate the temporal dynamics of
changes in individualism-collectivism. The use of content analysis of the Russian
language was justified to study individualistic and collectivist orientations in Ukraine
during the 20th century. Using correlation analysis between the usage of pronouns and
individualistic/collectivist words, it was demonstrated that the correlation is significant
only for those pronouns clearly associated with individualism-collectivism, which
indicates the relevance of studying pronoun usage to investigate this cultural syndrome.
Based on the study of the frequency of usage of all personal and possessive pronouns in
Russian (both in modern and pre-revolutionary orthography, totaling 114 words), it was
shown that Ukrainian society demonstrates a clear and statistically significant movement
towards increased individualistic orientations since the second half of the 1970s.

83
Collectivist orientations either remain unchanged over the study period or show a slight
decline.
7. One of the first attempts was made to apply change point analysis to study the
dynamics of linguistic data. Statistically significant change points correlate well with
major historical events in Ukrainian and Soviet history of the 20th century; this result
indicates that the dynamics of pronoun usage are a sensitive mechanism for society’s
response to significant historical events. It was shown that the "building of communism"
period (1918-1991) was characterized by a decreased individualistic orientation
compared to the preceding and succeeding periods. Notably, gradual changes
symmetrically encompass the beginning of this period (a sharp decline in individualism
begins in the mid-1920s) and its end (a sharp increase in individualism begins in the
mid-1970s). During this period, a brief surge in individualistic orientation coincides with
the Soviet-German War of 1941-45. The period of Stagnation is the longest period in the
20th century without statistically significant change points. The period of Perestroika on
the change graphs appears as a logical continuation of the transformations that began in
the second half of the 1970s.
8. Based on the analysis of data from the European Social Survey (European
Social Survey), specifically the results of the value orientations study using Schwartz’s
methodology, conducted in Ukraine from 2004 to 2012, it was shown that personal
values of Ukrainians demonstrate a statistically significant trend of growth over the
studied period, while collective values show a tendency to decrease.

84
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APPENDICES
Appendix A
Table А.1
Statistical Comparison of Models with Different Numbers of Factors
Model Cronbach’s
alpha χ²χ²/df GFI AGFI RMSEA
1-factor ?\0.67\0.74 1276\1584\
2126(1907)
2.75\3.4\
4.58(4.11)
0.63\0.81\
0.74
0.63\0.79\
0.71
?\0.07\0.084
(0.083)
2-factor
Ind.
Coll.
?\0.71\0.70
?\0.78\0.75
1066\1544\
1676(1504)
2.30\3.3
\3.62(3.25)
0.69\0.82\
0.80
0.69\0.79\
0.78
?\0.07\
0.072(0.075)
3-factor
Іnd.
HC
VC
?\?\0.70
?\?\0.69
?\?\0.64
?\?\1520(1367) ?\?\3.29(2.97) ?\?\0.83 ?\?\0.80 ?\?\0.068
3-factor ?\?\1537(1380) ?\?\3.33(2.99) ?\?\0.82 ?\?\0.79 ?\?\0.068

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Note: The results of Singelis et al. [51] \ Gouveia et al. [47] \ and the current study are presented (separated with \); values in
parentheses indicate results after the Satorra–Bentler adjustments; in all cases, the degrees of freedom (df) were as follows: 464 (for the
1-factor model), 463 (for the 2-factor), 461 (for the 3-factor), and 458 (for the 4-factor); p (χ²) < 0.0001 in all cases.