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Youngism: The Content, Causes, and Consequences of Prejudices Toward Younger Adults

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Abstract

Research on ageism has focused largely on perceptions of and biases targeting older adults, implicitly assuming that age-based stigma increases throughout the life span and that young adults benefit from favorable views relative to their older counterparts. In a series of eight studies (N = 2,323), we provide evidence to the contrary. We theorize that, in sharp contrast with ageism toward older adults, which revolves around fear and discomfort with the target’s later life stage, youngism (i.e., ageism toward young adults) is primarily generationally focused, aiming at contemporaneous generations of young adults rather than young adults in general. Consistent with this theorizing, we find that today’s young adults are ascribed a mixed stereotype content (Study 1a–1c), subject to harsher social judgments than both older age groups (Study 2) and recollections of former generations at the same age (Study 3a and 3b), and victim of discriminatory behaviors (Study 4 and 5). By comprehensively documenting cognitive, emotional, and behavioral evidence of youngism, the present work challenges the idea that ageism only reflects a plight of later-life aging. Instead, we show not only that ageism can target other age groups but also that the nature and content of ageism vary across the life span.
Journal of Experimental Psychology: General
Youngism: The Content, Causes, and Consequences of Prejudices Toward
Younger Adults
Stéphane P. Francioli and Michael S. North
Online First Publication, August 19, 2021. http://dx.doi.org/10.1037/xge0001064
CITATION
Francioli, S. P., & North, M. S. (2021, August 19). Youngism: The Content, Causes, and Consequences of Prejudices Toward
Younger Adults. Journal of Experimental Psychology: General. Advance online publication.
http://dx.doi.org/10.1037/xge0001064
Youngism: The Content, Causes, and Consequences of Prejudices
Toward Younger Adults
Stéphane P. Francioli and Michael S. North
Department of Management and Organizations, Stern School of Business, New York University
Research on ageism has focused largely on perceptions of and biases targeting older adults, implicitly
assuming that age-based stigma increases throughout the life span and that young adults benet from
favorable views relative to their older counterparts. In a series of eight studies (N= 2,323), we provide
evidence to the contrary. We theorize that, in sharp contrast with ageism toward older adults, which
revolves around fear and discomfort with the targets later life stage, youngism (i.e., ageism toward
young adults) is primarily generationally focused, aiming at contemporaneous generations of young
adults rather than young adults in general. Consistent with this theorizing, we nd that todays young
adults are ascribed a mixed stereotype content (Study 1a1c), subject to harsher social judgments than
both older age groups (Study 2) and recollections of former generations at the same age (Study 3a and
3b), and victim of discriminatory behaviors (Study 4 and 5). By comprehensively documenting cogni-
tive, emotional, and behavioral evidence of youngism, the present work challenges the idea that ageism
only reects a plight of later-life aging. Instead, we show not only that ageism can target other age
groups but also that the nature and content of ageism vary across the life span.
Keywords: age, anti-young ageism, generation, young adults, youngism
Supplemental materials: https://doi.org/10.1037/xge0001064.supp
Youth is a wonderful thing. What a crime to waste it on children.
George Bernard Shaw
Along with race and gender, age fundamentally underlies social
judgments and behaviors (Kite et al., 1991;Montepare & Zebro-
witz, 1998). Yet, despite the primacy of age, the consequences of
age-based categorization continue to be vastly understudied in
social psychology (Nelson, 2005,2017). One consequence of this
blind spot is a surprising lack of mainstream social psychological
theory unpacking the causes and consequences of stereotyping
across the full age spectrum. Terror management theory links age-
ism to mortality salience (Greenberg et al., 2002), sociological the-
ories to the advent of the printing press (Nelson, 2005),
evolutionary theories to the fear of illness (Kurzban & Leary,
2001), and a recent social-psychological resource competition per-
spective to generational tensions (North & Fiske, 2013). However,
in spite of purporting to explain the roots of ageism in general,
these theories emphasize prejudices targeting older adults, tacitly
assuming that older adults are the only targets of ageism and
thereby overlooking potential plights faced by the younger side of
the age spectrum.
Within a rapidly aging population, large cross-generational eco-
nomic inequalities have emerged: Todays young are the rst gen-
eration in modern history expected to do less well nancially than
their parents (Van Dam, 2020). Given the scolding of the young
generation in the public sphere and mainstream mediaexempli-
ed by the bashing of Millennials (e.g., Bauerlein, 2008;Stein,
2013) or backlash toward young political activists defending the
interest of their generation (e.g., Greta Thunberg, David Hogg,
Alexandria Ocazio-Cortez)the present is a particularly oppor-
tune time to address this gap in the literature.
The present article comprises multiple aims toward this end.
We theorize that, contrary to ageism toward older adults, which
largely results from ones anxiety regarding the targets late life
stage, youngism”—ageism toward younger adultsis genera-
tionally based, targeting contemporaneous generations of young
Stéphane P. Francioli https://orcid.org/0000-0002-2838-1146
Earlier versions of this work were presented at the East Coast Doctoral
Conference, the Transatlantic Doctoral Conference, the annual meeting of the
Academy of Management, the annual convention of the Society for
Personality and Social Psychology, the New York University (NYU) Stern
Alumni Reunion, and the annual conference of the International Association
for Conict Management.
This research was supported by a grant from NYU Sterns Doctoral
Student Engagement Fund. We thank Taylor Phillips, Beth Bechky, and
Joe Magee for their useful comments on earlier drafts. We also thank the
members of the M&O Work in Progress and the MIL Lab at NYU Stern for
their useful comments as this research was being developed. We also thank
Melanie Sequeira for her support preparing this article. Finally, we are
grateful to Anya Francioli for her proofreading contributions and her
encouragements throughout this research project.
Correspondence concerning this article should be addressed to Stéphane
P. Francioli, Department of Management and Organizations, Stern School
of Business, New York University, 44 West 4th Street, New York, NY
10012, United States. Email: sfrancio@stern.nyu.edu
1
Journal of Experimental Psychology: General
©2021 American Psychological Association
ISSN: 0096-3445 https://doi.org/10.1037/xge0001064
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adults specically, rather than young adults in general. In a series
of eight lab studies, we examine the modern perceptions of young
adults, show how they relate to unfavorable attitudes toward the
target group relative to older age groups and former generations of
young adults, and investigate how these generationally biased per-
ceptions may lead to prejudice and discrimination against todays
youth. We then discuss how the unique generational nature of this
bias may help illuminate our understanding of age-based social
cognition broadly, and we situate the current ndings relative to
the surprisingly long history of stereotyping younger generations.
Youthfulness: A Coveted Resource
Social psychological research offers little direct examinations of
lay peoples perceptions of young adults.
1
Instead, scholars have
typically incorporated younger adults into ageism research to
introduce a comparison group against which to pit older adult tar-
gets of focal interest (e.g., North & Fiske, 2013). This research,
looking at the effects of age on interpersonal judgments, suggests
that young adults may enjoy a more positive image than do older
ones (e.g., Drevenstedt, 1981;Lee & Clemons, 1985;Matyi &
Drevenstedt, 1989;Schwab & Heneman, 1978). A meta-analysis
(Kite et al., 2005) of 232 effect sizes from studies comparing
younger and older adult targets found that younger adults were
globally evaluated more positively, perceived as more attractive
and more competent, the target of less negative age stereotypes,
and subject to more favorable behaviors and behavioral intentions
than their older counterparts.
These ndings corroborate the general belief that young adults
possess valued attributes, in particular those associated with youth-
fulness (i.e., being in the primeof ones life). At a physical
level, youthfulness is synonymous with attractiveness, health,
strength, and vitality (e.g., Cross & Cross, 1971;Franzoi & Koeh-
ler, 1998). At an intellectual level, youth evoke intellectual curios-
ity, cognitive alertness, mental exibility, good memory, and
peaks in uid intelligence(Cattell, 1963;Craik & Salthouse,
2011;Crook et al., 1986;Horn, 1982;Horn & Cattell, 1967;
Zelazo et al., 2004).
When contrasted with the negative images associated with aging
(Cuddy et al., 2005;Cuddy & Fiske, 2002), the perks credited to
youthfulness provide powerful incentives for people to attempt to
maintain a youthful self-image. It may therefore come as no sur-
prise that older adults routinely dis-identify as old(Weiss &
Lang, 2009,2012) and that adults in general want to perceive
themselves as younger than they actually are, a discrepancy that
increases with age, and spans people in the United States (Barak &
Stern, 1986;Chopik et al., 2018;Goldsmith & Heiens, 1992;Mon-
tepare & Lachman, 1989), Europe (Öberg & Tornstam, 2001;
Uotinen, 1998;Westerhof et al., 2003); and Asia (Ota et al.,
2000). All in all, this desire for youthfulness across cultures sup-
ports the idea that it is universally perceived as a valued resource,
a resource well embodied by young adults.
A Darker Mainstream Portrait of Young Adults
Although social judgment and self-identity research on age sug-
gests that young adults may enjoy a positive imageparticularly
relative to that of older adultsthis conclusion seems at odds with
the depiction of contemporary youth disseminated in the public
sphere. As illustrated by recent best-selling books, such as The
Dumbest Generation (Bauerlein, 2008), Whats Wrong with Mil-
lennials? (Brown, 2013), and Not Everyone Gets a Trophy: How
To Manage Generation Y (Tulgan, 2009), a growing portrait paints
modern young adults as clueless and burdensome. This image reg-
ularly emerges in the form of derogating Millennials as narcissis-
tic, lazy, and entitled (e.g., Stein, 2013). In addition, Millennials
face blame for ruiningvarious societal standards, ranging from
high-level foundations such as democracy, marriage, work ethic,
and face-to-face interactions, to more trivial elements such as cere-
als, paper napkins, and wine corks (Agrawal, 2017;Bunnett, 2016;
Gifford, 2016;Schlossberg, 2016;Severson, 2016;Steverman,
2017;Williams, 2016). Beyond the negative image propagated in
the media, young adults report facing condescension in speech and
unfair workplace treatment due to their age, suggesting that the
social cognitions targeting this group may have deleterious, real-
world implications for its members (Duncan & Loretto, 2004;
Giles & Williams, 1994).
Although scant psychological research exists to speak to these
negative views of the young, some evidence appears to be consist-
ent with these anecdotal observations. For instance, a Q-sort task
conducted on undergraduates revealed both positive and negative
archetypes of young adults (Hummert, 1990). In a lexical-decision
task comparing positive and negative stereotypes targeting
younger and older adults, participants of all ages exhibited a posi-
tive bias toward olderbut not youngeradults (Chasteen et al.,
2002). A recent study also identied specic evaluator attributes
(i.e., people high on authoritarianism, people with high intelli-
gence, and well-read people) likely to lead to the disparagement of
young adults (Protzko & Schooler, 2019). Finally, outside of the
lab, a series of surveys and focus groups found that, across a wide
range of demographics, Americans describe contemporary youth
as undisciplined, disrespectful, unfriendly, irresponsible, and lack-
ing moral values (Farkas et al., 1997).
Life StageVersus Generational-Based Bias
Taken together, the combination of positive and negative per-
ceptions of younger adults highlights an apparent contradiction,
the young appearing both praised and disparaged. Reconciling
these competing views might point to the need to understand them
as complementary. Consistent with this reasoning, we propose that
the duality of young adultsimage results from two parallel proc-
esses of social categorizations: one based on young adultslife
stage and another based on young adultsgenerational afliation.
Age comprises theoretical underpinnings both universal and
exclusionarythat is, categories that are either permeable or
impermeable (Joshi et al., 2011;North, 2019). On the one hand,
1
Our denition of young adults was informed by peoples lay beliefs
about the target group. To determine who qualied as young adults,we
surveyed an age-diverse sample of 357 participants (189 women; 262
Caucasians; age: M=40.2,SD =13.31,Min. = 19, Max. = 78). Participants
identied young adults as people between M=18.0,SD = 3.85, 95% CI
[17.6, 18.4], and M=27.2,SD = 7.87, 95% CI [26.4, 28.1], a perceived age
bracket unaffected by participant age: correlation between participant age
and perceived lower age boundary of young adults: r=.008,p=.885;
correlation between participant age and perceived upper age boundary of
young adults: r=.071,p= .182. We used this bracket as our reference point
for this article.
2FRANCIOLI AND NORTH
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unlike race or gender, age is the only social category that com-
prises life stage subgroups that everyone eventually joins; pro-
vided sufcient life span, every living person will eventually
experience what it is like to be young, middle-aged, and older
(North & Fiske, 2012). On the other hand, age also comprises
impermeable, socially constructed generational clusters: Boomers
comprise only those born between 1946 and 1964, Generation X
those between 1965 and 1980, Millennials those born between
1981 and 1996, and so on (Dimock, 2019). Thus, unlike the uni-
versal experience of life stages, generational afliations foster
divisions between age cohorts: todays younger adults will never
know, for instance, what it was like to have come of age during
the Civil Rights Era, whereas older adults will never fully under-
stand growing up during the birth of smartphones.
Contrary to older-targeted ageism, which revolves around a fear
or discomfort with older adultslate life stage, young-targeted age-
ism likely does not center around young adulthood itself, a univer-
sally experienced and largely envied life stage. Instead, we propose
that youngism is generation-based, such that people purportedly
take exception with todaysyoung rather than young in general.
That is, people attribute to contemporary youth negative character-
istics that they believe didnt apply to previous generations at the
same age. Simply put, when it comes to ageism, people complain
about old peoplein general, but about kids these days!.
This theorizing suggests an overall mixed stereotype content of
young adultsthat is, a combination of positive and negative ster-
eotypes. Most social groupsdisadvantaged ones in particular
are subject to a mix of positive and negative generalizations about
its members, including women (Eagly & Mladinic, 1989;Glick &
Fiske, 1996;2001;Spence et al., 1979), African Americans (Czopp,
2008;Czopp & Monteith, 2006;Gaertner, & McLaughlin, 1983;
Kay et al., 2013), and older adults (Brewer et al., 1981;Chasteen et
al., 2002;Hummert, 1990;Levy, 1996). With regard to young
adults, we propose that the positive aspect of young adultsimage
likely mirrors peoples praise and envy for attributes such as beauty
and youthful energy, characteristics associated with young adults
life stage (i.e., young adulthood). On the other hand, the negative
aspect of young adultsimage speaks to a form of generational dis-
paragement, by which people see contemporary youth as less wor-
thy and deserving as former birth cohorts at the same age (i.e., a
perceived generational decline; Protzko & Schooler, 2019).
Youngism and Prior OldismFindings
If perceptions of the young are mixed and people are biased
against the young, as proposed above, then why did this phenom-
enon not clearly emerge in prior work? We propose that the spe-
cic comparative contextualization offered to participants in
classic age paradigms may help explain why previous research
singled out (older-focused) ageism but not youngism. To date,
social cognition researchers interested in age have primarily con-
ducted life-stage-based investigations, pitting attitudes toward
young adults in general and older adults in general in an effort to
maximize the generalizability of their ndings. Although valuable,
this approach may have overemphasized the life-stage categoriza-
tion of age targets and minimized the impact of the generational
categorization to which young adults are also subject.
In contrast, the present research focuses on a cohort-based
approach to young-targeted ageism, examining perceptions of and
attitudes toward todays young rather than young in general
(Trzesniewski & Donnellan, 2010). In so doing, we build upon
former work in social categorization theory to highlight the impor-
tance of temporal contextualization in age-related social cognition.
Social categorization theory has long established that categoriza-
tion is comparative and context-dependent (Turner et al., 1994). In
particular, introducing a comparison group or varying the nature
of that comparison affects the basis for social categorization
(Doosje et al., 1998;Haslam et al., 1992;Haslam & Turner,
1992). For instance, the basis for categorizing a young woman
may differ based upon whether she is compared with a young man
or an older woman; the process of social categorization, in turn,
denes the characteristics one ascribes to the target, the attitudinal
valence one feels toward it, and the set of behaviors one expects
from it (Van Rijswijk & Ellemers, 2002). Expanding on this litera-
ture to inform our understanding of ageism, we theorize that tem-
porally situated cohort labels (e.g., todays young adults) may
conjure up generation-based social categorization more strongly,
allowing evaluators to conciliate their negative attitudes toward
contemporaneous youth and belief in a generational decline with
the valued attributes of youthfulness that this social group histori-
cally epitomized.
Who Is More Likely to Espouse Youngist Beliefs (and
Why)?
Although familiar stereotypes about stigmatized groups pervade
societal strata, outgroup members are generally more likely to
uphold, express, and act on these stereotypes than are ingroup
members (Hewstone et al., 2002). Thus, as the strongest outgroup
members of the young, older adults constitute ideal candidates for
the endorsement of youngist beliefs.
Nevertheless, because we theorize that youngism stems from a
belief in generational decline over time, by which previous genera-
tions of young adults are perceived as having been better and more
deserving than contemporaneous ones (Protzko & Schooler,
2019), we expect older adultsdisparagement of younger genera-
tions to go beyond a simple outgroup effect and to represent more
than just one side of a reciprocal cross-generational derogation.
Instead, given our noted generational declinehypothesis, we
expect older adults to be more prejudiced toward younger genera-
tions than younger generations toward older ones. Also consistent
with a generational decline hypothesis (vs. mere ingroup-outgroup
derogation, or mutual generational disparagement), we predict that
older adults have unfavorable opinions of todays youth speci-
cally, but not of the youth of previous erasincluding the youth
of eras anterior to their own, considered outgroups too. In turn,
this negative stereotyping and derogatory generational comparison
targeting todays young should increase the tendency to attribute
youngs predicaments to their own wrongdoing, thereby justifying
generational inequalities and decreasing willingness to support
policies aimed at alleviating intergenerational imbalances. We
explore these predictions in a series of eight lab studies.
Research Overview
To explore lay perception of young adults, we rst examined
the stereotype content associated with todays young (Study
1a1c); we then compared attitudes toward the young with those
YOUNG-TARGETED AGEISM 3
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toward older contemporary age groups (Study 2), other prejudi-
cially targeted social groups (Study 3a), and former generations of
young adults (Study 3a and 3b); nally, turning to practical con-
cerns, we documented the unique prejudicial and discriminatory
consequences of youngism, highlighting the detrimental effect of
endorsing certain stereotypes about younger generations on ones
willingness to support a political candidate with a future genera-
tionoriented speech (Study 4) and ones likelihood to fund a uni-
versitys student debt relieve initiative (Study 5).
Study 1a: Modern Stereotype Content of Young
Adults Inductive Approach
Combining inductive and deductive methods (Burisch, 1984;
Hinkin, 1995;Tskhay et al., 2018), we rst built a model of the
stereotype content of young adults. This task served four purposes:
to gain a deeper understanding of the perceptions of the target
group, to conrm that they are subject to a mixed stereotype con-
tent, to obtain a validated stereotype measure for subsequent stud-
ies, and to provide a comprehensive model that can serve as a
building block for future research on youngism.
Taking an inductive approach, we conducted a principal compo-
nent analysis (PCA) to reduce a large, participant-generated pool
of adjectives associated with young adults to a manageable set of
the most representative items (Study 1a). Taking a deductive
approach, we complemented this condensed set of participant-gen-
erated items with a list of author-generated ones, based on former
research and common media descriptions of young adults. We
then subjected the combined set of items to an Exploratory and
Conrmatory Factor Analysis (EFA and CFA; Study 1b). The out-
putresulting from a total of 1,081 participantsforges a model
of young adult stereotype content. We then tested the predictive
power of the model (Study 1c) and conducted additional valida-
tion, robustness checks, and exploratory analyses, the details of
which are reported in Supplemental Materials 18.
Method
Item Generation
Fifty-one Amazon Mechanical Turk workers (25 women; 44
Caucasians; age: M= 38.2, SD = 10.92, Min. = 22, Max. = 66)
2
each listed ve adjectives they thought were most representative
of todays young adults. This process generated 137 unique valid
items90 attributes appeared more than oncea pool size con-
sistent with prior bottom-up scale development using a similar
methodology (e.g., Lin et al., 2005).
This initial pool reected a broad array of dimensions, from per-
sonality-based attributes (e.g., courageous, creative, arrogant, dis-
tracted) to cognitive abilities and knowledgeability (e.g., intelligent,
smart, slow, uninformed), and comprised a mix of 45 positive
items, 20 neutral ones, and 72 negative ones, as coded by two
research assistants blind to the goal of this study, Cohensj=.704,
p,.001 (see Supplemental Material 1 for a full list of generated
items; see Supplemental Material 2 for a large replication of the
item generation survey, providing support for the representativity of
the items in this initial list, and conrming the accessibility of the
items retained and relevance of the ensuing model).
Participants
Six hundred forty-one responses were collected via Amazon Me-
chanical Turk. Fifty-eight responses (9.0%) were excluded for failing
to complete at least one attention check and/or completing the study
multiple times, leaving a sample of 583 participants (295 women;
465 Caucasian; age: M= 38.6, SD =11.11,Min. = 19, Max. =74).
3
Given the age-related nature of our research, we strived to
obtain a broad age distribution for our sample. We applied an age
quota, such that roughly a third of our respondents were between
18 and 35, another third between 36 and 55, and a last third 56 and
above. The quotas were set based on respondentsage, a piece of
information that the potential respondent provided in a short lter
questionnaire completed prior to entering the study, or as part of
preliminary questionnaires conducted by the crowdsourcing plat-
form. When the quota was met for one of these three age catego-
ries, following respondents from that age category would be
precluded from entering the study and invited to enroll in another
study without an age restriction. Unless explicitly mentioned, sim-
ilar age lters were used for subsequent studies.
Measure and Procedure
Participants stated the extent to which they believed that each of
the 138 items previously generated applied to young adults using a
7-point scale (1 = Strongly Disagree,7=Strongly Agree). Two
attention checks were included in this study. They were embedded
among the items of a scale at the end of the survey and read This
is an attention check, please select [one/seven] and move to the
next item.We included the same type of attention check across
all studies included in this article.
4
Results
In line with recent recommendations (Osborne et al., 2014), we
conducted a parallel analysis (PA) and minimum average partial
criteria analysis (MAP) to determine a-priori factor solutions. The
parallel analysis was conducted on FACTOR (Lorenzo-Seva &
Ferrando, 2006) and suggested a six-factor solution. The MAP test
was performed on SPSS using OConnors (2000) code. The origi-
nal MAP test (Velicer, 1976) proposed a 13-factor solution,
whereas the revised MAP test (Velicer et al., 2000) proposed a 12-
factor solution. We rst explored the data using the most liberal of
these solutions (i.e., the 13-component solution proposed by the
revised MAP test).
5
We conducted a PCA using an oblimin
2
In all studies, respondents completed the study in exchange for money,
at a price estimated pre-hoc based on expected average completion time, at
a rate of $0.10 to $0.15 per minute.
3
In this study and the following ones, we took a conservative approach
toward duplicate participants. Respondents were considered duplicates
when their IP address was identical to that of another respondent. In such
case, both responses were excluded from further analyses.
4
Study 1a and 1b and Study 4 were conducted under the following IRB
approval (UCAIHS): IRB-FY2016-540, Age and Generation Diversity at
Work. Study 1c, 2, 3a, 3b, and 5, as well as all online supplemental material,
were conducted under the following IRB approval (UCAIHS): IRB-FY2018-
1357, Youngism.
5
Twenty-one components possessed an Eigenvalue superior to 1.
However, we discarded the Eigenvalue threshold as a viable solution, given
the proven strength of PA and MAP over the Eigenvalue approach in
selecting factors (Osborne et al., 2014).
4FRANCIOLI AND NORTH
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rotation, an optimal rotation choice to effectively identify items
associated with each factor as well as simple structures when pres-
ent (Finch, 2006). We discarded items with strong double-loading
and items loading below .40 on their respective primary compo-
nent. We also discarded components with fewer than three items
and components with no items loading above .50. In all, we
retained 57 items.
Study 1b: Modern Stereotype Content of Young
Adults Deductive Refinement
The 57 participant-generated items retained at the end of Study
1a were complemented with 36 items produced by the authors
(Hinkin, 1995; see Tskhay et al., 2018 for a similar method). This
complementary deductive process aimed at addressing certain lim-
itations of the participant-generated list, such as adding common
media depictions of young adults that were missing in the partici-
pant-generated pool (e.g., narcissistic, geeky), and including theo-
retically relevant items based on themes explored in former
academic research on young adults. For instance, inspired by prior
work on generational perceptions (e.g., Twenge, 2013), we added
items such as civic-mindedto assess whether young adults
social engagement represents a central theme in peoples percep-
tion of the target group (see Supplemental Material 1 for full list
of generated items).
6
We merged the two sets of items (93 items)
and subjected them to a series of EFA and CFA using a new sam-
ple of participants.
Method
Participants
Four hundred seventy-eight responses were collected via Ama-
zon Mechanical Turk. Thirty-two responses (6.7%) were excluded
because the respondents failed to complete one or several attention
checks, or completed the study multiple times, leaving a sample of
447 participants (258 women; 379 Caucasians; age: M= 46.2,
SD = 14.34, Min. = 19, Max. = 83).
Measure and Procedure
The procedure was similar to that of Study 1a. Participants were
asked to state the extent to which each of the 93 items applied or
not to young adults, using a 7-point scale (1 = Strongly Disagree;
7=Strongly Agree).
Results
The parallel analysis suggested a six-factor solution while the
MAP analysis proposed an 11-factor solution. We conducted a
Principal Axis Factor analysis with an oblimin rotation using the
PA and MAP results as the lower and upper boundaries for our
nal factor solution. We screened factors and items using rules
similar to those described in Study 1a.
Eight factors encompassed within two higher-order factors
emerged. We used these exploratory analyses as a screening pro-
cedure to guide selection of a smaller set of items, both for the
sake of parsimony, and to facilitate the subsequent use of more so-
phisticated analytic techniques (see Glick & Fiske, 1996; for a
similar approach). In the nal model, we retained 10 items for
each of the two higher-order factors, using the most representative
items of each of the subfactors.
An initial CFA was performed to assess the degree of t of the
proposed model on the current dataset. We employed structural
equation modeling techniques on AMOS Version 27.0 (Arbuckle,
2020). Because the model was developed using the same dataset,
this preliminary CFA cannot be considered an independent test of
t (see Appendix A for CFA results of Study 1b and all subse-
quent studies). Nevertheless, the analysis still offered support for a
solution with two higher-order factors each encompassing four pri-
mary factors. The rst higher-order factor was largely positive
(i.e., resourceful facet: smart, ambitious, hip, and techie) and the
second one largely negative (i.e., ungrateful facet: coddled disre-
spectful, rookie, and radically progressive; see Figure 1). In line
with comparative practices used in other SEM scale-development
studies (e.g., Glick & Fiske, 1996;Luhtanen & Crocker, 1992),
these same t indices were considerably worse for a one-factor
model. Our nal model also outperformed a two-factor model
(i.e., keeping only the two higher-order factors) and a four-factor
model (i.e., isolating the radically progressive and techie factors,
which displayed comparatively weaker loadings on their higher-
order factors, and grouping the remaining 16 items under their re-
spective higher-order factors). Furthermore, the Akaike Informa-
tion Criterion (AIC) of the nal model was within the vicinity of
that of the saturated model with both small and moderate size sam-
ples. Finally, the reliability of the factors included in the nal
model was moderate to high, and Cronbach alphas within accepta-
ble range (see additional tables in Supplemental Material 3 for
detailed statistical properties). Similar analyses on following sam-
ples further supported these conclusions.
Study 1c: Modern Stereotype Content of Young
Adults Initial Predictive Validity of the Model
In Study 1c, we assessed the predictive power of the model
developed in Study 1a and 1b. The purpose of this assessment was
threefold. First, we tested whether the endorsement of the cognitive
content identied in Study 1a and 1b predicted attitudes toward the
young. Second, we explored the complementarity of the eight sub-
factors retained in our nal model. Third, we assessed whether our
model predicted attitudes toward that target group above and
beyond warmth and competence, universalalbeit nontarget spe-
cicdimensions of social cognition (Fiske et al., 2002).
Method
Participants
We collected 375 responses from the crowdsource platform Pro-
lic.co. We excluded incomplete and duplicate responses, as well
as respondents who failed our attention checks. The nal sample
included 358 participants (176 women; 270 Caucasians; age:
M= 44.08, SD = 15.90, Min. = 18, Max. = 80).
6
The items emerging in the replication survey available in
Supplemental Material 2 corroborate the choice of our author-generated
items.
YOUNG-TARGETED AGEISM 5
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Procedure and Measures
Participants rst reported their attitudes toward twenty social
groups using 11-point, single-item thermometers (5=Extremely
cold feelings;þ5=Extremely warm feelings). The social groups
included fteen llers (e.g., female professionals, the Asian Amer-
ican community, pro-life activists, politicians) and ve targets (i.
e., todays young adults, Millennials, people in their 20s, college
students, and young professionals), presented in random order.
Prior research suggests that the stereotype content associated with
a target group may vary based on the label or subtarget category
employed (Van Rijswijk & Ellemers, 2002). We measured atti-
tudes toward ve young target groups (a) to ensure that our nal
model was comprehensive enough to predict attitudes toward
young adults independent of minor label variations and (b) to
assess whether the predictive power of the eight subfactors
unearthed in our nal model varied across different young adult
subpopulations.
After completing the attitude thermometers, participants were
told that they would be randomly assigned to two of the twenty
social groups they just evaluated and would provide a more in-
depth opinion of these two groups. In reality, all participants were
assigned to todays young adultsand African Americans.
Using a 7-point scale (1 = Strongly Disagree; 7=Strongly Agree),
they reported the extent to which the 20 items of the stereotype
content developed in Study 1a and 1b applied to young adults
today (see Appendix B for an illustration of the scale) as well as
the extent to which they felt that todays young were warm (warm,
friendly, seless, and empathetic; a= .85) and competent
(competent, condent, ambitious, and assertive; a= .75). The
evaluation of African Americansaller group included to
reduce risks of demand characteristicmimicked the format
employed for young adults, using positive and negative adjectives
taken from Peabody (1967).
Results
We converted attitude measures on a 100-point scale, and
standardized all continuous predictors, such that every regres-
sion coefcient represents the change in attitude toward the tar-
get group, in percentage points, for a participant scoring 1 SD
above the mean on that given predictor. Results reported in
Table 1 and 2include a general measure of attitudes toward
young adults (i.e., a single measure collapsing attitudes toward
the ve target groups). Table 3 provides a breakdown for each
target groups. Detailed results at the subfactor- and facet-level
are described below.
Subfactors of the Stereotype Content and Attitudes
Toward Young Adults
The eight subfactors predicted attitudes toward young adults in
the expected direction, with the exception of the radically progres-
sive subfactor (see Table 1), not pointing conclusively in any
direction. A follow-up regression revealed that, although not sig-
nicant on its own, the latter subfactor interacted with partici-
pantspolitical views, such that conservatives, who held more
negative attitudes toward young adults to begin with, B=4.36,
Figure 1
Full Model of the Stereotype Content of Young Adults
Note. On the one hand, young adults are praised for their perceived resourcefulness, a mix of youthful energy (ambitious), high level of uid intelli-
gence (smart), and adaptability to the current time (hip and techie). On the other hand, they are depicted as ungrateful: an overly protected group
(coddled) at the bottom of the totem pole (rookie) that inappropriately challenges older generations (disrespectful), cherished norms, and established
authority (radically progressive).
6FRANCIOLI AND NORTH
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p,.001, 95% CI [6.33, 2.39], h
p
2
= .051, 95% CI [.015, .101],
were even more likely to do so when they believed young adults
were radically progressive, B=1.89, p= .037, 95% CI [3.66,
.12], h
p
2
= .012, 95% CI [.000, .044]. In this sense, although the
radically progressivelabel need not be negative in and of itself,
the very people who interpret it as such (i.e., conservatives) are the
ones upholding negative views of young adults in the rst place.
We then assessed the complementary predictive power of the
subfactors in two ways. First, we examined their ability to comple-
mentarily predict attitudes toward young adults in general (see Ta-
ble 2). Multiple subfactors of our stereotype content remained
signicantly predictive when entered jointly in a single model
(model 1, 3, and 5a), even when participants demographics and
general response to attitude thermometers were included in the
model (model 5b).
7, 8
Second, we tested whether the eight subfac-
tors varied in predictive power across our ve target groups, nd-
ing evidence supporting the utility of incorporating all eight
subfactors (see Table 3). For instance, hip was especially predic-
tive of attitudes toward college students, but far less of those to-
ward Millennials or todays young adults. In contrast, techie was
particularly predictive of attitudes toward Millennials, and coddled
of those toward people in their 20s.
The Two Facets of the Stereotype Content and Attitudes
Toward Young Adults
The resourceful and ungrateful facetscombining the 10 items
of each facetwere associated with attitudes toward young adults
in the expected direction when entered separately; B= 10.76,
-p,.001, 95% CI [9.15, 12.36], h
p
2
= .328, 95% CI [.253, .398]
(resourceful facet, Table 2, model 2), and B=7.83, p,.001,
95% CI [9.61, 6.05], h
p
2
= .174, 95% CI [.108, .243] (ungrate-
ful facet, model 4).
We also expected the two facets of our stereotype content to
predict attitudes toward young adults above and beyond warmth
and competence. Prior to testing this prediction however, we rst
examined the correlations between the two facets of our model on
the one hand, and warmth and competence on the other, as a pre-
liminary test of convergent/divergent validity (see Supplemental
Material 6 for an in-depth test). Although the correlations were
generally high, consistent with other recent work comparing dif-
ferent stereotype content subdimensions (e.g., Hentschel et al.,
2019), it is worth noting that warmth and competence both showed
large positive correlations with the resourceful facet and moderate
negative correlations with the ungrateful facet. In this sense,
because the resourceful facet of our model does not map neatly
onto either warmth or competence any more than does the ungrate-
ful facet, our overall model demonstrates divergent validity from
SCM dimensions (Kervyn et al., 2015; see also correlation matri-
ces in Supplemental Material 4a, 4b, and 5 for a general corrobora-
tion of these ndings).
To examine the predictive power of our model relative to
the SCM, we then inputted these measures into a series of
multiple regressions. The facets of our model were comple-
mentary predictive of attitudes toward young adults (Table 2,
model 6a), even when controlling for participant's demo-
graphic characteristics and general response to attitude ther-
mometers (model 6b). In contrast, although warmth and
competence were complementary predictive (model 7a), the
competence dimension became nonsignicant when control
variables were added (model 7b). Finally, when included
jointly with warmth and competence (model 8a & 8b), the two
facets of our model remained signicant and directionally
consistent, suggesting that their predictive power extended
beyond that of the two universal but nontarget-specic
dimensions of social perceptions. We replicated these results
in three additional studies using different operationalizations
of warmth (/communality) and competence (/agency; see
Supplemental Material 4a, 4b, and 5), including one using 20
Table 1
Descriptive Statistics and Correlational Matrix, Study 1c
Descriptives Correlations
Variable MSDAttitudes Warm Competent
Resourceful facet 5.10 0.80 .57 .65 .73
Smart 4.96 1.07 .54 .60 .64
Ambitious 4.57 1.16 .52 .68 .69
Hip 4.87 1.20 .33 .33 .42
Techie 6.34 0.77 .18 .12 .26
Ungrateful facet 4.73 0.97 .42 .55 .31
Coddled 4.76 1.45 .40 .52 .25
Disrespectful 4.48 1.24 .42 .51 .23
Rookie 4.96 1.19 .30 .46 .36
Radically progressive 4.81 1.02 .02 .04 .05
Warm 4.31 1.09 .59 ——
Competent 4.77 0.92 .48 .61
Correlation between the resourceful and ungrateful facets .39
Note. All correlations were significant at p,.001, except for Techie/Warm, and Radically Progressive/Competent, significant at p,.05, and Radically
Progressive/Warm and Radically Progressive/Attitude, nonsignificant.
7
General response to attitude thermometers was measured by collapsing
responses to attitude thermometers of the 15 ller targets. The measure was
included in an effort to control for risks of systematic error variance
(Podsakoff et al., 2003).
8
Importantly, despite the large number of variables entered in the
models, the variance ination factors (VIFs) were all below 3, mitigating
concerns over potential multicollinearity among variables (Hair et al.,
2006;Menard, 1995;Kutner et al., 2004).
YOUNG-TARGETED AGEISM 7
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Table 2
Predictive Properties of the Two Facets of the Stereotype Content of Young Adults on Attitudes Toward the Target Group
Variable Model 1 Model 2 Model 3 Model 4 Model 5a Model 5b Model 6a Model 6b Model 7a Model 7b Model 8a Model 8b
Smart 5.90*** 4.55*** 2.75**
Ambitious 4.80*** 3.38** 2.33*
Hip 1.73
2.64** 1.27
Techie 0.79 1.10 0.61
Coddled 2.95* 2.01 2.81**
Disrespectful 4.93*** 3.44** 2.88**
Rookie 1.88
0.61 0.29
Radically progressive 1.34 0.80 0.71
Resourceful facet 10.76*** 9.09*** 4.95*** 5.53*** 3.16***
Ungrateful facet 7.83*** 4.28*** 5.13*** 2.22* 3.50***
Warmth 8.90*** 7.19** 5.80*** 4.46***
Competence 3.65*** 0.96 0.79 0.36
Age 1.80* 1.78** 1.33
1.08
Female 1.47 2.28
0.79 1.38
Education 0.39 0.22 0.63 0.59
Conservatism 1.78* 1.91* 3.51*** 1.98**
Control groups 10.51*** 10.44*** 9.94*** 9.94***
R
2
.34*** .33*** .20*** .17*** .39*** .65*** .37*** .63*** .37*** .62*** .42*** .65***
Highest VIF 2.04 1.00 2.86 1.00 2.90 2.95 1.18 1.48 1.58 1.84 2.53 2.69
Note. VIF = variance inflation factor. Continuous predictors are all standardized. Attitude thermometer (dependent variable) converted to a 0 to 100 scale, with 0 = Extremely Cold and 100 =
Extremely Warm.
p= .1. * p= .05. ** p= .01. *** p= .001.
8FRANCIOLI AND NORTH
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items, to match the stereotype content of our nal model
(see Supplemental Material 5).
Additional Analyses and Scale Validation
We further tested the properties and structural validity of
the model developed in Study 1a-b using a metasample
compiling 4,812 unique participants from various studies con-
ducted over the course of this research program (see
Supplemental Material 6), conrmed the convergent validity
of the model via a correlational study with a set of common
prejudice measures (see Supplemental Material 7), and con-
ducted additional assessments of the utility of the model by
comparing its predictive power against social dominance ori-
entation, a more generic antecedent of prejudice (Ho et al.,
2015;Pratto et al., 1994;seeSupplemental Material 4a and 8).
Taken together, these additional analyses support the useful-
ness of the factors and subfactors retained as well as the over-
all robustness of the model.
Discussion
Responding to a call for a more granular descriptive under-
standing of the phenomena studied in psychology (Cooper,
2016), the model emerging from Study 1b presents a detailed
account of the key dimensions of the stereotype content of
young adults, offering a general mixed image of the target
group. On the one hand, perceptions of young adults include
the advantageous attributes of their youth (i.e., resourceful
facet): Participants associate younger adults with a peak in
cognitive skills (i.e., intelligence) and energy (i.e., ambition),
as well as with being keenly in tune with the time (i.e., hip and
tech-savvy). On the other hand, people also ascribe negative
stereotypes to younger adults (i.e., ungrateful facet), perceiv-
ing the target group as naïve (i.e., rookie), overly reliant on
previous generations (i.e., coddled), and inappropriately chal-
lenging toward current norms and authority (i.e., disrespectful
and radically progressive). Whereas the resourceful facet
reects envied attributes of youthfulness such as vigor, cogni-
tive abilities and adaptability, the ungrateful facet, depicting
young adults as dependent and rebellious, speaks to noted
power imbalances relative to older generations.
As per ndings of Study 1c, these two overarching facets
were distinct fromand predicted attitudes toward young
adults above and beyondperceptions of warmth and compe-
tence, two universal, albeit nontarget-specic, dimensions of
social cognition (Fiske et al., 2002). In addition, although the
resourceful and ungrateful facets of our model constitute a stat-
istically parsimonious way of capturing participantsendorse-
ment of the stereotype content of young adults, the eight
subdimensions of the model displayed complementary predic-
tive power and helped account for the nuances in stereotype
content associated with some specic subpopulations of that
broader target group. These more granular eight subdimensions
may therefore reveal useful to researchers aiming at studying
perceptions of specic subpopulations of young adults (e.g.,
college students vs. young professionals, Millennials vs. Gen
Z). That said, additional work is needed to further clarify the
function of each of these subdimensions, particularly with
regard to the distinct attitudes and behaviors they may predict.
Acknowledging this opportunity for future investigations, we
focus the remainder of this article on the two higher-order
dimensions of the model to better understand the causes and
consequences of these mixed perception of young adults.
Study 2: Perceptions of Different Age Groups
The mixed stereotype content unearthed in Study 1 suggests that
evaluators may be subject to a form of cognitive bias against young
adults. However, given prior ndings that older adults also face
mixed stereotype content (Cuddy et al., 2005;Fiske et al., 2002), it
remains uncertain how perceptions of todays young map onto those
of other age groups. Indeed, people may still harbor favorable atti-
tudes toward todays young relative to older counterparts. In Study 2,
Table 3
Predictive Properties of the Stereotype Content of Young Adults on Attitudes Toward Each Young
Target Group
Variable Today's YA Millennials People 20s College stud. Young pro.
Smart 4.91*** 4.47** 3.97** 5.20*** 4.18**
Ambitious 3.73* 4.07** 2.48
2.36 4.28**
Hip 1.65 1.93
2.42* 4.48*** 2.73*
Techie 0.02 3.12** 0.64 1.85
1.12
Coddled 3.08
2.48 4.42** 2.95
2.88
Disrespectful 4.65** 4.44** 1.92 2.61 3.59*
Rookie 0.46 1.12 0.14 2.28
0.93
Radically progressive 0.48 0.05 1.66
0.48 2.28*
R
2
.35*** .34*** .28*** .29*** .27***
Highest VIF 2.90 2.90 2.90 2.90 2.90
Note. All predictors are standardized. Attitude thermometers (dependent variables) converted to a 0 to 100
scale, with 0 = Extremely Cold and 100 = Extremely Warm.
Today's YA = today's young adults; People 20s = people in their 20s; College stud. = college students; Young
pro. = young professionals; VIF = variance inflation factor.
p= .1. * p= .05. ** p= .01. *** p= .001.
YOUNG-TARGETED AGEISM 9
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we tested for this possibility by comparing attitudes toward different
adult age cohorts.
Method
Participants
We collected 300 responses via Amazon Mechanical Turk, a
sample size estimated based on previous developmental psychology
work using a similar type of paradigm (e.g., Heckhausen et al.,
1989). We excluded duplicate responses and respondents who
failed our attention check. The nal sample included 293 partici-
pants (169 women; 233 Caucasians; age: M= 45.29, SD =15.04,
Min. = 18, Max. =82).
Procedure and Measures
Participants shared their attitudes toward various age cohorts.
To reect the inherently continuous nature of age and best cap-
ture potential curvilinear relationships, we asked participants to
evaluate virtually all age cohorts composing the adult popula-
tion, presenting target age groups in 10-year increments (i.e.,
people currently in their 20s, 30s, 40s, and so on, up to people
in their 90s). Participants reported their attitudes toward each
target age group using attitude thermometers (1 = Extremely
cold feelings;11=Extremely warm feelings).
Results
We compared participantsattitudes toward different age
cohorts by regressing attitudes toward target group on age of
the cohort (i.e., people in their 20s, 30s, etc.). Standard errors
were clustered at the participant level to accommodate the
within-participant design of our analysis. We centered the in-
dependent variable (i.e., target cohorts age) and, as per Study
1c, transformed the dependent variable (attitude thermome-
ters) into a 100-point scale, to obtain more easily interpretable
size effects.
We regressed attitudes on target age cohorts and calculated
estimates for different target age cohorts using Statasmargin
function. Overall, attitudes toward the target cohort became
gradually more positive as cohortsage increased, such that
the cohort in its 90s (M= 74.18, SE = 1.49) earned 14% more
positive regard than the cohort in its 20s (M= 64.98,
SE =1.12;seealsoTable 4 model 1, and Figure 2a). We tested
for alternative models in which we included the quadratic
Table 4
Attitudes Toward Various Age Cohorts, Study 2
Model 1 Model 2
Variable BSE 95% CI BSE 95% CI
Constant 69.58 0.95 [67.72, 71.44] 69.58 0.92 [67.78, 71.39]
Age cohort (c) 0.13 0.03 [0.08, 0.18] 0.13 0.03 [0.08, 0.18]
Participant age (s) 3.98 0.91 [2.19, 5.77]
Participant Age (s) 3Age Cohort (c) 0.13 0.02 [0.09, 0.18]
R
2
.02 .07
Note. Age cohorts are centered, and participant age is standardized. Attitude thermometers converted to a 0 to
100 scale, with 0 = Extremely Cold and 100 = Extremely Warm. All predictors significant at p,.001.
Figure 2
Attitudes Toward Various Age Cohort on a 0 to 100-Point Scale, Study 2
Note. (a) Attitudes toward various age cohorts. (b) Attitudes toward various age cohorts as a function of participant age (1SD = 30-year-old partici-
pants; +1 SD = 60-year-old participants).
10 FRANCIOLI AND NORTH
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term of target age cohorts to allow for nonlinear relationships:
The quadratic term was not signicant.
9
Of note, and consist-
ent with our prediction that older adults would be more biased
toward younger ones than the other way around, this increase
in favorable attitudes for older target cohorts was moderated
by participant age, such that younger participants tended to
show more homogenous evaluations across target age groups,
and older participants displayed higher attitudinal divides
between younger and older target cohorts, with marked prefer-
ence for older targets (see also Table 4 model 2, and Figure
2b). Notably, however, the biggest evaluative difference
between younger and older participants was crystalized in
their attitudes toward older target groups, not younger ones,
toward whom attitudes seemed more consensualand on the
lower end relative to other target age groups.
Discussion
Using a repeated measure design devised to assess attitudes to-
ward different age cohorts, Study 2 offers evidence that people
harbor colder feelings toward todays young adults than toward
any contemporary older age group, including old-old adults. Fur-
thermore, although older participants show a form of ingroup-out-
group bias, we nd less evidence of an ingroup preference or
strong outgroup derogation from younger participants, who eval-
uated all age cohorts relatively similarly. In Study 3a and 3b, we
claried the nature of this youngism bias, testing our prediction
that the effect is generational, applying to contemporary youth
specically.
Study 3a: The Generational Dimension of Youngism
Study 3a sought to achieve ve goals. First, we compared atti-
tudes toward current and former generations of young adults,
expecting participants to exhibit colder feelings toward young
adults today specically, rather than toward all generations of
young over time. Second, we compared attitudes from younger par-
ticipants (i.e., adults age 18 to 35) and older participants (i.e., adults
56 and older), expecting unfavorable attitudes toward contemporary
youth to be driven by the evaluations of older participants. Third,
we also compared attitudes toward current versus former genera-
tions of older adults, expecting the negative generational bias
against contemporary young not to apply to contemporary older tar-
gets. Fourth, we compared attitudes toward current versus former
generations of women, African Americans, and Asian Americans,
to conrm that generational bias against contemporary targets did
not apply to other stereotyped social groups. Finally, we examined
the role of participantsendorsement of the stereotype content of
todays young developed in Study 1, expecting the ungrateful facet
associated with generational rather than life stage characteristics
of todaysyoungto explain the differential in attitudes toward
current versus former generations of young adults.
Method
Participants
Two hundred nineteen responses were collected via Amazon
Mechanical Turk. Thirty-two responses were excluded because the
respondents failed to complete one or several attention checks, or
completed the study multiple times, leaving a sample of 99
younger participants (49 women; 74 Caucasians; age: M= 27.5,
SD = 4.56, Min. = 18, Max. = 35) and 88 older participants (62
women; 74 Caucasians; age: M= 62.2, SD = 4.93, Min. = 56,
Max. = 80).
Procedure and Measures
Participants assessed their attitudes toward ve target groups
(people in their 20s, people in their 60s, African Americans, Asian
Americans, and women) using 11-point feeling thermometers as in
Study 2. For each target group, participants assessed current gener-
ations (e.g., people currently in their 20s) immediately followed
by a similar assessment for previous generations (e.g., previous
generations in their 20s), resulting in a total of ten evaluations.
Participants then completed the 20 items of the stereotype content
developed in Study 1, followed by a basic demographic
questionnaire.
10
Results
For each target, we conducted on G*Power 3.1 conducted a
two-way mixed ANOVA comparing attitudes of younger versus
older participants (between-subjects factor) toward current versus
former generations of the target group (within-subject factor). We
followed with post-hoc LSD tests to analyze interactions. As in
prior studies, we converted the thermometer to a 100-point scale
to ease effect size interpretation. Results are summarized in
Table 5.
A sensitivity analysis conducted on G*Power 3.1 suggested
that, with our sample size, two participant groups, two repeated
measurements, a measurement correlation of r=.50, a power
of .80, and an a= .05, we could capture an effect size as small
as h
2
=.022(Faul et al., 2007;Faul et al., 2009). Younger par-
ticipants did not differ signicantly in their attitudes toward
people currently in their 20s (M=54.14,SD = 13.47) and for-
mer generations in their 20s (M=54.85,SD =12.01),p= .814,
but older participants did, reporting lower attitudes toward peo-
ple currently in their 20s (M=54.20,SD = 10.94) relative to
previous generations at the same age (M=61.82,SD =6.92),
p= .017 (see interaction, F[1, 185] = 5.02, p= .026, h
p
2
= .026,
95% CI [.000, .087], no interaction in other models were signif-
icant). These results contrast with attitudes toward the older
age group target: Despite a notable in-group out-group differ-
ence, F(1, 185) = 27.62, p,.001, h
p
2
= .130, 95% CI [.052,
.221], both younger and older participants expressed more
favorable feelings toward people in their 60s today (M= 63.85,
SD = 10.00) than toward previous generations at the same age
(M=60.80,SD =10.18),F(1, 185) = 6.31, p= .013,
h
p
2
= .033, 95% CI [.001, .097]. As predicted, no difference in
current versus former generations emerged for Asian American
and women targets. Contrary to our expectations, participants
9
More complex models appear in Supplemental Material 9. The
supplementary analyses provide additional nuances but support the general
conclusions reported in the main Results and Discussion sections.
10
Participants also completed three items (a= .79) pertaining to the
clarity of the items in the study, to ensure that the current versus previous
generation items were not confusing. Participants overwhelmingly stated
that the questions were clear: M= 4.36 (of 5), SD = 0.72.
YOUNG-TARGETED AGEISM 11
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showed warmer feelings toward former generations of African
Americans (M=61.34,SD = 11.22) than toward current ones
(M=58.61,SD = 12.24), although this difference was much
smaller than that for the young adult target, F(1, 185) = 3.96,
p= .048, h
p
2
= .021, 95% CI [.000, .026].
11
Turning to endorsement of the stereotype content of todays
young adults, we regressed attitudes toward people in their 20s
endorsement on the two facets of the stereotype content devel-
oped in Study 1b (standardized), target generation (current gen-
eration = 1, former generation = 0), and the interactions of each
facet with target generation, clustering data at the participant
level to account for our within-subject design. The current gener-
ation of young adults was evaluated signicantly less favorably
than former generations at the same age, B=.40, p= .009,
95% CI [.69, .10]. The resourceful facet was a signicant
predictor of attitudes toward the young age group target, B= .38,
p= .023, 95% CI [.05, .71], and was not moderated by target
generation, B= .23, p= .232, 95% CI [.15, .61]. In contrast,
the ungrateful facet was not a signicant predictor on its own,
B= .23, p= .147, 95% CI [.08, .54], but was strongly moder-
ated by target generation, B=.52, p= .002, 95% CI [.84,
.20], such that the gap between current and former generations
increased with endorsement of the ungrateful facet.
12
Discussion
Older participants reported colder feelings toward people cur-
rently in their 20s than toward former generations at the same age.
In contrast, younger and older participants alike reported warmer
feelings toward people currently in their 60s than toward former
generations at the same age. This stark difference (i.e., relative
unfavorable attitudes toward current young adults but relative
favorable attitudes toward current older adults) highlights the gen-
erational, cohort-based (vs. life-stage-based) nature of ageism tar-
geting young adults.
13
In addition, the preference for former
relative to current generations identied for the young age group
target seems much more pronounced for this social group than for
any other commonly discriminated group we tested, suggesting
that these generational differences may be more characteristic of
prejudice toward the young.
Finally, the resourceful facet of the stereotype content of young
adults predicted attitudes toward young adults, regardless of their
generational belonging. This nding tends to indicate that the favor-
able attributes associated with young adults are largely perceived as
applying to all generations. That is, they are universal characteristics
inherent to young adulthood. In contrast, the ungrateful facet of the
stereotype content was specically predictive of contemporary young
adults, indicating that the unpleasant attributes associated with young
adults are perceived as unique to the current younger generation
rather than to people in the younger life stage in general.
Table 5
Attitudes Toward Current Versus Former Generations of Various Social Groups as a Function of Participant's Age Group
Participant age group Current versus previous generations Interaction
Younger participants Older participants
Model
Younger
participants
Older
participants
Current
generation
Previous
generations
Current
generation
Previous
generations
Delta
Current
generation
Previous
generations
Delta
Target group F F M SD M SD F M SD M SD F M SD M SD Sig. MSDMSDSig.
People in their 20s 3.06*** 1.72 54.49 12.7 58.01 9.36 7.29** 54.17 12.26 58.13 10.03 5.02* 54.14 13.47 54.85 12.01 54.2 10.94 61.82 6.92 *
People in their 60s 4.95*** 27.62*** 56.11 11.27 69.32 6.16 6.31* 63.85 10 60.8 10.18 0.06 57.78 11.5 54.44 11.01 70.68 5.67 67.95 6.62
African American 4.26*** 0.12 59.49 13.08 60.51 10.21 3.96* 58.61 12.24 61.34 11.22 0.15 58.38 13.24 60.61 12.98 58.86 11.2 62.16 9.15
Asian American 5.96*** 0.4 61.52 9.92 63.35 8.78 0.38 62.09 9.33 62.67 9.49 1.4 61.82 9.61 61.21 10.32 62.39 9.12 64.32 8.49
Women 4.04*** 6.97** 65.86 9.46 71.82 4.27 0.96 68.13 8.21 69.2 6.68 0.39 65.66 10.51 66.06 8.45 70.91 4.83 72.73 3.71
Note. Attitude thermometers (dependent variables) converted to a 0 to 100 scale, with 0 = Extremely Cold and 100 = Extremely Warm.
Delta Sig. = post-hoc tests examining differences in attitude scores between current and previous generation targets.
*p= .05. ** p= .01. *** p= .001.
11
More favorable attitudes toward former generations of African
Americans possibly reect a form of particular respect and admiration for
older Black citizens, who in some ways epitomize the Civil Rights
movement.
12
Supplemental Material 10 provides an extended model including 3-
way interactions with younger versus older participants. The results are
consistent with the ones provided in the main text
13
See Supplemental Material 11 for a replication of these ndings using
an alternative paradigm.
12 FRANCIOLI AND NORTH
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Although the paradigm of Study 3a allowed us to test a large range
of predictions, it left open the possibility that older adults may have
thought of themselves when assessing former generations of young
adults,such that the effect reects a simple outgroup bias, rather
than a broader set of ageist beliefs and perception of generational
decline. Study 3b focused on older adults only and was designed
with the specic goal of ruling out this alternative outgroup
hypothesis.
Study 3b: Evidence of Perceived Generational Decline
In Study 3b, older adults shared their opinion of young adults
from different eras, including older outgroup cohorts at this earlier
life stage (e.g., young adults from the 1940s). This design allowed
us to compare two competing hypotheses: The outgroup bias hy-
pothesis, which predicts that older adults will show a marked pref-
erence toward their generation when they were young than toward
young adults from generations both anterior and posterior to theirs;
and a cohort-based youngism hypothesis, focused on a sense of
perceived generational decline, which predicts that older adults
will display more favorable attitudes toward young adults of past
erasincluding young from their own generation and other past
generationsthan toward todays younger adults.
Method
Participants
We collected 101 responses from U.S.-based participants age
50 and above, via Prolics crowdsourcing platform. One partici-
pant was excluded because their age did not meet our initial
recruitment screening (i.e., age = 38). None of the participants
failed our attention check, yielding a nal sample of 100 partici-
pants (56 women; 85 Caucasians; Age: M= 60.45, SD = 7.04,
Min. = 50, Max = 78).
Procedure and Measures
Using a series of single-item thermometers with endpoints
5=Extremely unfavorable opinion, and þ5=Extremely favor-
able opinion, participants reported their attitude toward young
adultsdened as people age 18 to 28from ve different eras:
young adults from the 1940s, 1960s, 1980s, early 2000s, and
young adults today. Note that our oldest participant was born in
1942; and most were born in the 1950s through 1960s, such that
no participants would be considered an in-group member of our
oldest target cohort (i.e., young adults in the 1940s). Order of
cohort eras was counterbalanced across participants.
Results
We ran a one-way, repeated-measure ANOVA to examine older
adultsattitudes toward younger adults of our six eras (i.e., 1940s,
1960s, 1980s, 2000s and nowadays). Attitude thermometers were
converted to a 100-point scale. A sensitivity analysis conducted
using G*Power 3.1 indicated that, with our sample size, six
repeated measurements, a measurement correlation of r= .43, a
power of .80, and an a= .05, we could capture an effect size as
small as h
2
= .011. As predicted, the era factor was strongly signif-
icant, F(4, 396) = 35.79, p,.001, h
p
2
= .113, 95% CI [.055,
.166]. A post hoc analysis revealed that young adults from the
1940s (M= 77.3, SD = 18.19) were ratedtentativelymore
favorably than those from the 1960s (M= 73.5, SD = 21.53,
D=3.8, p= .111), and young adults from the 1960s were rated
similarly as those from the 1980s (M= 72.6, SD = 18.51, D=.9,
p= .706). The latter were rated more favorably than young adults
from the early 2000s (M= 65.9, SD = 21.51, D=6.7, p= .005),
who were rated barely more favorably than todays young adults
(M= 62.6, SD = 28.06, D=3.3, p= .166). Taken together, a con-
trast between former and recent generations of young adults offers
perhaps a better t to the data, whereby attitudes toward young
adults pre-2000 (i.e., 1940s to 1980s; M= 74.5, SD = 19.51) were
higher than those toward young adults post-2000 (i.e., 2000s and
2020s; M= 64.3, SD = 24.99), D=9.8, F(1, 396) = 44.22,
p,.001.
14
Discussion
In a within-subject design assessing older adultsattitudes to-
ward young adults from different eras, participants showed marked
preferences for young adults of earlier eras, even rating the oldest
cohort (i.e., young adults from the 1940s) similarly or higher than
their own cohort at this same life stage. These results contradict
the notion that youngism from older adults represents a mere
ingroup-outgroup bias, suggesting instead preference for former
generations and a derogation of contemporary young adults
specically.
In our last two studies, we go beyond cognitive and attitudinal bias
to examine potential real-world implications of youngism. Speci-
cally, we propose that stereotype endorsement about young adults
desensitizes people to the struggles faced by todays younger genera-
tions and reduces peoples willingness or likelihood to address con-
temporary generational inequalities.
Study 4: Youngism and Willingness to Address
Growing Generational Inequalities
In light of growing intergenerational inequalities and concerns
over the lack of solvency of federal programs geared toward older
adults, some have argued for a renegotiation of the generational
contract to better the prospects of future generations (e.g., Inter-
generational Commission, 2018). In this regard, political ofcials
may take a powerful role by advocating for economic and social
policies geared toward reducing inequalities between younger and
older adults; on the other hand, politicians are often constrained in
their decisions, votes, and public views by the opinion of the elec-
torate they are bound to represent. In Study 4, we expected that
endorsement of the stereotype of young adults would be associated
with voting intentions toward a politician promoting policies
aimed at improving the younger generations prospects. In this
sense, we sought not to just gauge attitudes but instead to capture
behavioral intentions that would affect real-world outcomes aimed
at rectifying generational imbalances.
14
Complementary analyses (see Supplemental Material 12), including
the treatment of independent variables as a single continuous measure, the
use of an ingroup bias variable, and the inclusion of demographic controls,
all provide results consistent with those reported here.
YOUNG-TARGETED AGEISM 13
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Method
Participants
Two hundred twenty responses were collected via Amazon
Mechanical Turk. Given the Studys focus on American poli-
tics, only U.S. citizens were allowed to participate. Duplicate
responses and respondents who failed the attention check were
excluded. The nal sample included 178 participants (91
women; 152 Caucasians; age: M=41.1,SD =12.39,Min. =18,
Max. =73).
15
Procedure and Measures
Participants rst shared their endorsement of the stereotype
content of young adults. They then completed a habituation
task in which they successively evaluated four anonymized,
brief quotations taken from recent U.S. political speeches,
paraphrased from candidates in the 2016 Presidential Election.
For each quotation, participants shared the extent to which the
statement made them want to vote for the (anonymous) candi-
date, and the extent to which it made them want to vote
against the candidate. The quotes covered broad social and
economic issues and were meant both to habituate participants
to sharing their opinion about anonymous political candidates
based on their speech, and to reduce risks of demand charac-
teristics by confounding the purpose of the study and increas-
ing time between predictors and dependent variable.
The main task followed the short habituation activity. Partici-
pants read a 275-word statement, ostensibly excerpted from a lon-
ger speech pronounced by an anonymous political candidate
running for national ofce. The statement emphasized the need to
address youth unemployment, reduce student debt and act proac-
tively to increase the engagement of young Americans in the soci-
etal and political life of their country (see Appendix C). The
speeches from the habituation task and the main task were crafted
in large part by paraphrasing speeches from political candidates
during the 2016 U.S. Presidential campaign, in an effort to
increase the external validity of the paradigm.
After reading the excerpt, participants completed a series of be-
havioral intention items designed to capture their hypothetical
engagement for or against the candidate, followed by a brief de-
mographic survey.
Stereotyping of Young Adults. Participants completed the 20
items of the stereotype content developed in Study 1. As in previ-
ous studies, the 10 items of the resourceful facet and the 10 items
of the ungrateful facet were averaged into two composites.
Behavioral Intentions. The behavioral intention measure
comprised 12 items appraising participantslevel of support
for the candidate. Six items captured participantssupport
(e.g., [this speech] would make me more likely to vote for
this candidate,”“[this speech] would make me more likely to
give money to this candidatescampaign). Six other items
measured participantsdegree of opposition (e.g., [this
speech] would make me more likely to vote against this candi-
date,”“[this speech] would make me more likely to give
money to the campaign of an opponent to this candidate;full
scale items available in Appendix C). Participants responded
to these items using a 5-point scale (1 = Not at all true, 5=
Completely true).
16
We reverse-coded the six items measuring
the engagement against the candidate and combined them with
the six items measuring the engagement in favor of the candi-
date to form a scale of candidate support (a=.87).
Results
We regressed general support for the candidate on the two fac-
ets of the stereotype content and the demographic variables (i.e.,
age, gender, and education). A sensitivity analysis conducted on
G*Power 3.1 indicated that, with our sample size, a power of .80
and an a= .05, and a total of ve predictors, we could capture an
effect size as small as h
2
= .052. The model was signicant, F(5,
172) = 12.79, p,.001, R
2
= .271, 95% CI [.147, .355]. The demo-
graphic variables did not emerge as statistically signicant predic-
tors. The resourceful facet positively predicted participants
engagement for the candidate, B= .30, p,.001, 95% CI [.21,
.40], h
p
2
= .191, 95% CI [.096, .291], and the ungrateful facet nega-
tively predicted it, B=.10, p= .004, 95% CI [.17, .03],
h
p
2
= .048, 95% CI [.005, .122].
Discussion
Above and beyond the predictive power of participant age,
endorsement of the stereotype content of todays young affected
behavioral intentions, such that participants strongly endorsing the
ungrateful but only weakly endorsing the resourceful stereotypes
were less likely to support a political candidate offering a future-
generation-oriented speech. These results conrm that bias against
young adults may have important real-world consequences vis-à-
vis rectifying generational imbalances. That said, this study did
not directly measure behavior. Furthermore, despite the presence
of an interim habituation task, the studys purpose may have still
been identiable by participants. Study 5 addresses these limita-
tions and explored youngism outside of the political context by
using a direct behavioral measure in a charity allocation paradigm.
Study 5: Youngism and Funding of a Student Debt
Relief Charity
In our last study, we examined the effect of stereotype endorse-
ment on behaviors by looking at peoplesnancial support for a
student debt relief initiative. Between 2003 and 2017; student debt
has increased by 385% (Federal Reserve Bank of New York,
2018), becoming a major nancial burden for todays younger
generations. It has also gained prominence in the national U.S. po-
litical debate in recent years (Berman, 2019). We predicted that
endorsement of the stereotype content of todays young would pre-
dict the likelihood to fund a university-based charity helping stu-
dents deep in debt.
15
A non-negligible percentage of respondents failed the attention check
in this study (15%). However, additional analyses reincluding these
participants suggest that the results presented in this article are not
signicantly affected by this ltering procedure.
16
Because a technical error, three items capturing the engagement in
favor of the candidate and three items capturing the engagement against the
candidate were measured on a 7-point scale instead of a 5-point scale. The
responses to these 6 items were converted into a 5-point scale post hoc to
match the scale of the other items.
14 FRANCIOLI AND NORTH
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Method
Participants
Two hundred twenty-eight U.S.-based respondents partici-
pated via Prolic Academic. Two respondents who failed the
attention check and one respondent who failed to appropriately
disclose her age were excluded. The nal sample included 226
participants (119 women; 177 Caucasians; age: M= 42.7,
SD = 14.96, Min. = 18, Max. = 78).
Procedure and Measures
Participants completed a two-part study, as in Study 2. The rst
part of the study was similar to our alleged opinion survey on con-
temporary American society. Participants shared their opinion
about a ller group, followed by young adults, followed by a sec-
ond ller group, all supposedly randomly selectedfrom a pool
of 24 target groups. Christian Americans and African Americans
were used as ller groups and displayed in random ordereither
before or after young adults target. Participants then completed a
few additional ller items about modern U.S. societyto reinforce
our cover story of a social survey on contemporary American soci-
etyas well as basic demographic items.
Upon completing the demographics, participants were redir-
ected to a new survey (i.e., the second part of our study), presented
as an ostensibly unrelated online questionnaire about a university-
based charity initiative taking place at the researchersinstitution.
To increase realism, this second questionnaire used a different lay-
out, including the font, color code, and logo of a notable east coast
U.S. university. The prompt informed participants that the
researchers pledged to give $0.25 to two on-campus charities for
each participant who takes part in their study. Participants were
then invited to select two out of four mock charities to which their
donation would be sent on their behalf. One of the charities
focused on student debt (i.e., New York Universitys Student Debt
Fund. Help New York University students who incur particularly
high level of debt to fund their study). The other three were unre-
lated to the target group (e.g., New York University's Historic
Preservation Fund. Help the University nance the preservation
and restoration of its historical buildings.). The charity selection
concluded the study.
Stereotyping of Young Adults. As part of the opinion sur-
vey, participants completed the same 20-item young adult stereo-
type content measure as prior studies in this paper, using a 7-point
scale (1 = Strongly Disagree,7=Strongly Agree).
Funding of the Student Debts Charity. Participantsselec-
tion of the student debt relief charity in part two of the study served as
our binary dependent variable (i.e., 0 = no funding;1=funding).
Results
We conducted a binomial logistic regression to assess the predict-
ability of participantsendorsement of the stereotype content of todays
young adults on their choice to fund the on-campus student debt char-
ity, controlling for participant age, gender, and years of education,
v
2
(5) = 25.88, p,.001, Pseudo R
2
= .095. A sensitivity analysis con-
ducted on G*Power 3.1 suggests that, with our sample size, a power
of .80 and an a= .05, we could capture an effect size equal to or larger
than OR = 1.49 for the resourceful facet and equal to or smaller than
OR = .67 for the ungrateful facet. Continuous variables were standar-
dized to interpret the constant. The constant, B=.71,p= .001, indi-
cates that a majority of people opted to give money to the student debt
relieve initiative, perhaps a reection of the perceived primary goal of
a university (i.e., to offer students the possibility of an education).
Women were marginally more likely to nance the charity, B=.59,p
= .061, OR = 1.81, 95% CI [.97, 3.38], and older participants were
marginally less likely to do so, B=.31, p= .054,
OR = .73, 95% CI [.54, 1.01]. Participants who scored +1 SD above
the mean on endorsement of the resourceful facet were approximately
50% more likely to fund the charity, B=.42,p= .015, OR =1.52,
95% CI [1.09, 2.14], and participants who scored +1 SD above the
mean on endorsement of the ungrateful facet were approximately 25%
less likely to fund the charity, B=.33, p= .057, OR =.72,95%CI
[.52, 1.01].
Discussion
As expected, controlling for participant age, gender, and years
of education, young-targeted ageism predicted the likelihood that
participants direct their donation to a student-debt charity rather
than to charities unrelated to helping the target group. These nd-
ings offer direct behavioral evidence of the detrimental effect of
youngism, complementing the attitude and behavioral intention
evidence of the preceding studies.
General Discussion
Theoretical and empirical work examining the role of age in
social perception has focused almost exclusively on the plight of
older adults, implicitly assuming that age stigma increases
throughout the life span, such that one faces growing age-based
stigmatization as one progressively loses valued attributes associ-
ated with youthfulness. The present work challenges this assump-
tion, offering a rst comprehensive set of empirical evidence that
ageism also affects adults on the early side of the age spectrum.
In addition, these studies show that the nature and content of
ageism vary across the life span. Contrary to social biases against
older adults, which center around peoples discomfort with aging
be it symbolic (terror management theory, Greenberg et al.,
2002) or tangible (resource tensions, North & Fiske, 2013)per
the current ndings, biases against the young entails a strong gen-
erational dimension, an ascription that facilitates comparative bias
and disparagement of current youth. We discuss the implications
of these ndings in the following sections.
Youngism: A Missing Piece of the Ageism Puzzle
By comprehensively documenting cognitive, emotional, and be-
havioral evidence of ageism against young adults, the present
work offers support that youngism is a real, consequential, yet
understudied phenomenon. It is of particular theoretical impor-
tance: Just like our understanding of gender perception would be
incomplete without a solid grasp of underlying attitudes toward
men (Glick et al., 2004;Glick & Fiske, 1999), our comprehension
of age in social cognition is limited by a lack of knowledge of
young-targeted ageism. It is also of practical importance: In rap-
idly aging nations, young adultswho represent the future of
these societiesare progressively becoming a minority whose life
YOUNG-TARGETED AGEISM 15
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outcomes may not be at par with those of previous generations and
whose interests may be less well represented. For these reasons,
the present work addresses the apparent one-sidedness in the study
of age perceptions.
Per our examination of the nature of youngism, the distinct form of
age bias targeting the young seems to respond partly to lay concerns
over perceived birth cohort differences and generational decline. We
identify two key implications of these ndings for the study of ageism.
First, the birth cohort distinction uncovered in these studies may help
explain why young-targeted ageism did not emerge as strongly in prior
age research (e.g., Kite et al., 2005), the way it does in the present
work. Given evidence provided in our analyses (particularly Study 3a
and 3b) that people purport to derogate the present youth specically,
it stands to reason that attention to temporal contextualization (present
youth vs. former youth) may play an important role in bringing to light
anti-young ageism. This consideration is worth noting for researchers
interested in studying young-targeted social perception in the future.
Second, these results also highlight the need to better discrimi-
nate between distinct yet intertwined components of age. Other
scholars have previously alluded to this issue, arguing that age
comprises a variety of elements, including chronological age, sub-
jective age, social age, generational afliation, and life stage, to
name but a few (Joshi et al., 2011;Kooij et al., 2008;North, 2019;
Weiss & Lang, 2009,2012). Nevertheless, social psychological
research, scant on the subject of age perception to begin with, gen-
erally lacks this nuanced perspective. This oversight renders it dif-
cult to pinpoint precisely which aspect(s) of age contributes to
shape social perception. The current article begins to ll this void
by demonstrating that both life stage and generational afliation
shape target age perception. In doing so, we stress the importance
of temporal contextualization in age-based social cognitions. Dif-
ferentiating current from former members of a given group allows
for a switch in social categorization, with a focal on generational
rather than life stage comparison, the former offering more latitude
to disparage a group one may have formerly been a proud member
of but does not identify with anymore. In this regard, the effects of
temporal contextualization are likely to be particularly salient in
age research; contrary to gender and race, every living person nav-
igates from one age group to the next over time.
Of note, the fact that young are partly disparaged for their gen-
erational afliation rather than life stage contrasts with prior work
elucidating the older side of the age spectrum, in which older
adults view their own generational afliation more positively than
their own life stage (Weiss & Lang, 2009). The reverse pattern
between younger and older age groups emphasizes how disentan-
gling the effects of various age-related constructs may allow future
researchers to better identify what age-based constructs matter the
most in driving social perception and related prejudices (North,
2019). Distinguishing between cohort and life-stage differences
more broadly is a growing scholarly subeld (e.g., Yang, 2008), to
which the current ndings also contribute.
Youngism: An Old Prejudice?
The present set of studies focused primarily on contemporary views
of age groups and birth cohorts; that is, our experiments speak to cur-
rent perceptions of todays young and how these perceptions are
unattering relative to contemporary perceptions of todays older age
groups and contemporary perceptions of former generations of young
adults (see Study 2, 3a and 3b). One may therefore wonder whether
youngism is a new phenomenon uniquely targeting todays young, or
whether former generations were subject to similarly harsh social judg-
ments in their 20s and 30s. That is, is each generation under the illu-
sive impression that the generation succeeding them is not as worthy
as their own, or are Millennials the rst generation to be subject to
such a perception of generational decline?
Although our empirical work does not offer a direct answer to
this question, historical evidence of the consistency of criticisms
toward younger generations may hint at an answer. Indeed, dispar-
agements of the younger generation trace all the way back to An-
cient Greece: In the words of the poet Esiode (800 BC), I see no
hope for the future of our people if they are dependent on the friv-
olous youth of today, for certainly all youth are reckless beyond
words(as cited by Seder, 2013). Similar derogatory comments
can be found throughout history (Ruggeri, 2017;Seder, 2013;
Standage, 2006). Anecdotally, this derogatory generational com-
parison is well illustrated by the proverbial statement Kids these
days...,a complaint generally attributed to older adults implying
that previous generations were betterthan the new one.
Recent empirical ndings backup this claim. In ve studies,
Protzko and Schooler (2019) found that someone who objectively
exceled in a domain was more likely to both notice othersfailings
on that domainincluding the youngand to incorrectly assume
that all members of her generation used to do better on that domain
when they were young than do current young, giving the illusion
of a generational decline. The universality and atemporality of
these mechanisms further bolster the argument that generational
disparagement likely occurred for millennia.
The stereotype content of young adults unveiled in our own
work provides further indirect support and offers additional nuan-
ces. As the epigraph of this article implies, perceptions of the
young have most likely always contained positive and ungrateful
elements. However, in spite of this persistence throughout history,
there is reason to believe that certain aspects of the stereotype con-
tent associated with this group have likely evolved over time. For
instance, the presence of a factor such as tech-savviness in the
resourceful facet of our modelwhich responds optimistically to
the regularly broadcasted, admonished impact of technology and
social media on contemporary youthwould have likely not been
part of the stereotype content of young adults a few decades ago.
Instead, it may have been replaced by a factor referring to young
adultsearly adoption of technologyor habitsfrom that time.
Therefore, the stereotype content ascribed to the younger genera-
tion at a given time likely reects the societal hopes and fears of
the social changes taking place at this time. In support of this argu-
ment, historical accounts offer examples of 18th century intellec-
tuals admonishing the growing interest of youth for novels and
plays, a hobby seen as corrupting moral character and preventing
the youth from developing useful knowledge; comparable
thinkers, a century later, castigated younger adults for their passion
for chess, a form of mental gladiatorshipkeeping the youth
away from outdoor exercises (see Reverend Enos Hitchcock,
1790, & Scientic American, 1859; as cited by Seder, 2013). Most
parents today might encourage these two activities, chastising the
use of social media and video games.
Yet, some components of the stereotype content of young adults
might also be relatively stable, reective of biological attributes
specic to youthfulness (e.g., energy and physical tness) as well
16 FRANCIOLI AND NORTH
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as enduring structural relations between younger and older adults
across civilizations (e.g., perceived disrespect due to young adults
adoption of new social norms). In this regard, the radically pro-
gressive subdimension that emerged in our model maps onto left-
radicalism critiques of former young generations; for instance, the
now conservative-leaning Baby Boomers were criticized for simi-
lar supposedly naïve political behaviors as pioneers of the counter-
culture and New Left in the 1960s and 1970s (Richardson, 2012).
Future research might therefore consider delving into archival
data sets or news articles depicting the younger generation, in
search of whether the ambivalent allianceascribed to young
adults has indeed persisted for centuries, and whether and how its
content has morphed over time to blend with the societal changes
of each particular time. Regardless of how temporally constrained
youngism may be, the phenomenon is undoubtedly of growing im-
portance in a rapidly aging world, fraught with rising generational
tensions over scarce economic, political, and environmental
resources. As a rapidly aging society grapples with record-high
levels of generational coexistence, the potential for unpacking the
extent of youngism over time also increases.
Opportunities for Future Research
The present work opens multiple opportunities for future research.
First, extending on the above comment, exploring how the content of
the stereotypes and intensity of the biases toward the young evolved
over time may help determine whether such a phenomenon as worsen
as the population is aging. It may also help identify other potential ex-
acerbating factors, such as rapid social and technological changes, that
may increase intergenerational tensions.
Results of Study 1c also revealed variations across different young
target groups along the eight subfactors of our model. These varia-
tions suggest that people may not see the broad and diverse popula-
tion of young adults as a monolith, but rather, distinguish subgroups
(e.g., Millennials, Gen Z, College students, university-educated
entry-level professionals, young workers with low education back-
ground) toward whom they harbor distinct attitudes and opinions.
Additional research may help better understand how this large social
group is further delineated by laypeople, and how distinct views of
these subgroups may reect divergent societal ideals and inform dif-
ferent policy-support aimed at shaping the trajectory of younger gen-
erations and the future of the societies they will one day lead.
Complementarily, researchers may be interested in examining
how the stereotype content identied in Study 1 and attitudes toward
different age groups and generations reported in Study 2 and 3 hold
up cross-culturally. Contradicting prevailing beliefs that Eastern cul-
tures hold older adults in higher esteem than do Western cultures, a
meta-analysis by North and Fiske (2015) found a higher level of dis-
paragement toward older adults in Eastern culture. In light of these
ndings, three competitive predictions may apply to attitudes toward
young adults across cultures. One may surmise that biases targeting
young and old are positively correlated, reective of a broad general
age-based stigmatization, such that youngism may be more preva-
lent in cultures already high on oldism.Alternatively, ageism tar-
geting older and younger adults may be negatively related, reective
of intergroup tensions among generations, leading one to conclude
that societies holding higher biases against older adults may be less
likely to disparage the young. Finally, the distinct mechanisms
underpinning youngism and oldism may lead one to conclude that
the two forms of ageism are unrelated, rendering any educated guess
harder with regard to estimating level of youngism cross-culturally.
As noted, as generational dynamics rapidly change around the
world, the opportunities for psychological research on attitudes to-
ward younger adults will become all the more salient.
Conclusion
The current article offers a systematic investigation of young-targeted
ageism: its unique causes as well as its deleterious behavioral conse-
quences. The ndings provide both an enhanced understanding of mod-
ern attitudes toward the young as well as an explanation for the plight of
young adults, in which derogatory comparison relative to former birth
cohorts at the same age reinforces their disadvantaged standing. From a
theoretical standpoint, the current work illustrates how young-targeted
ageism is driven primarily by cohort-based beliefs that the current
younger generation is lacking relative to prior ones, in contrast with
older-adult-targeted ageism, which is driven primarily by life-stage
(rather than cohort-based) beliefs. By providing a detailed descriptive
stereotype content, documenting cognitive, emotional, and behavioral
biases against younger adults, and highlighting the unique generational
dimension of these biases, the current work hopes to inspire formative
lines of work on young-targeted ageism. Such is necessary in an increas-
ingly multigenerational and aging worldone that is ever dependent on
the solvency and viability of its youngest members.
Context of the Research
This project emerged as an extension of a growing body of
research on stigmatization of older adults, which is formative but
overlooks the full potential age spectrum of these biases. In an
aging society in which young adults are progressively becoming a
minority, the way in which younger generations are perceived and
treated by society is increasingly important. We wrote this article
with the dual purpose of offering a practical impetus and theoreti-
cal basis to pursue more work on the stigmatization of younger
adults. We hope that it will contribute to broaden our understand-
ing of ageism and age-related social cognition and help contextual-
ize age stigmatization from a real group conict perspective, in
which the role of stereotyping of younger and older adults is inter-
preted in the context of scarce economic and political resources
that must be shared by an increasingly larger and more age- and
generationally diverse population. The solvency of contemporary
society depends on our ability to maintain a delicate balance
among various generationsneeds and desires. In the future, we
hope to extend this line of work by illuminating the link between
ageism targeting young and old, as well as by building a stronger
understanding of youngism across cultures and throughout history,
in an effort to further identify exacerbating and inhibitory factors.
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(Appendices follow)
20 FRANCIOLI AND NORTH
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Appendix A
Goodness of Fit for the Final Model, Study 1b5
(Appendices continue)
Study NModel CMIN/DF GFI CFI RMSEA AIC
Study 1b 447 Final model 2.3 .922 .952 .053 462
4-factor model 6.3 .799 .794 .109 1,122
2-factor model 8.2 .747 .712 .127 1,460
1-factor model 13.5 .415 .494 .168 2,378
Independence model 23.2 .346 .000 .223 4,440
Study 1c 358 Final model 2.2 .909 .956 .057 447
4-factor model 5.9 .797 .811 .117 1,055
2-factor model 7.6 .754 .736 .136 1,370
1-factor model 15.3 .518 .424 .200 2,689
Independence model 23.3 .296 .000 .250 4,465
Supplementary Material 4a 280 Final model 3.0 .850 .882 .084 577
4-factor model 4.6 .793 .785 .113 840
2-factor model 6.3 .728 .673 .137 1,140
1-factor model 11.0 .532 .368 .190 1,967
Independence model 15.3 .374 .000 .226 2,948
Supplementary Material 4b 228 Final model 2.6 .842 .914 .084 518
4-factor model 4.5 .736 .810 .124 831
2-factor model 6.3 .681 .705 .153 1,145
1-factor model 12.4 .427 .357 .224 2,198
Independence model 17.0 .286 .000 .265 3,261
Supplementary Material 5 359 Final model 2.2 .909 .952 .058 455
4-factor model 5.0 .821 .839 .106 912
2-factor model 6.8 .762 .760 .127 1,226
1-factor model 14.4 .522 .438 .193 2,537
Independence model 22.4 .306 .000 .245 4,299
Supplementary Material 6 (Meta-analysis) 4,812 Final model 18.7 .937 .947 .061 3,109
4-factor model 72.0 .801 .785 .121 11,893
2-factor model 96.5 .742 .702 .141 16,395
1-factor model 195.9 .511 .386 .201 33,571
Independence model 286.4 .319 .000 .244 54,465
Supplementary Material 7 169 Final model 1.7 .863 .946 .065 372
4-factor model 2.9 .784 .850 .107 572
2-factor model 3.9 .722 .769 .131 737
1-factor model 8.0 .463 .490 .204 1,447
Independence model 12.1 .282 .000 .257 2,338
Study 2 (& Supplementary Material 8 & 9) 293 Final model 2.2 .892 .945 .063 448
4-factor model 5.2 .768 .798 .120 946
2-factor model 6.3 .728 .673 .137 1,140
1-factor model 10.7 .502 .518 .182 1,894
Independence model 19.0 .290 .000 .248 3,644
Study 3a 187 Final model 1.8 .867 .935 .066 389
4-factor model 3.7 .747 .775 .121 703
2-factor model 4.3 .718 .716 .134 816
1-factor model 8.1 .515 .394 .195 1,458
Independence model 11.5 .326 .000 .237 2,223
Study 4 178 Final model 2.5 .796 .911 .092 504
4-factor model 4.1 .735 .819 .133 768
2-factor model 5.0 .684 .764 .149 919
1-factor model 11.3 .398 .375 .242 2,015
Independence model 15.9 .236 .000 .290 3,054
Study 5 226 Final model 2.1 .871 .929 .068 632
4-factor model 5.2 .733 .721 .136 939
2-factor model 6.1 .695 .649 .150 1,110
1-factor model 9.8 .525 .382 .198 1,760
Independence model 13.9 .565 .000 .239 2,675
Note. AIC = Akaike information criterion. All confirmatory factor analyses were conducted on AMOS, Version 27.0 (Arbuckle, 2020). Models were esti-
mated using Maximum likelihood. AIC for the saturated model = 420. The final model, the 4-factor models, and the 2-factor model are all described in
details in the Results section of Study 1b. The 1-factor model included the 20 items of the final model under a single factor. Heywood cases emerged in
the initial estimation of the final model in Supplementary Material 4a, Study 4, and Study 5, and the estimation of the 4-factor model in Study 3a. These
cases were likely a reflection of the small size of these samples (i.e., N,300; Chen et al., 2001;Joreskog & Sorbom, 1984) and were resolved using rec-
ommendations from Gaskin (2016).
YOUNG-TARGETED AGEISM 21
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Appendix B
Young AdultsStereotype Content Scale
To what extent do you agree or disagree with the below state-
ments about young adults?
Todays young adults are...
Eager
Motivated
Driven
Bright
Intelligent
Sharp
Stylish
Fashionable
Internet-savvy
Tech-savvy
Entitled
Spoiled
Pampered
Condescending
Argumentative
Snobbish
Inexperienced
Unseasoned
Leftists
Socialists
Appendix C
Material, Study 4
[...]Weneedtodomoretoght youth unemployment,
because what we are doing now is turning our backs on an
entire generation of young people who want to get a job.
They want to earn some income, they want to get out of
their homes, they want to become independent, and we are
not allowing them to do that. We are not giving them the
chance they deserve. This election is about understanding
that if we do not transform our economy, our younger gen-
eration will likely have a lower standard of living than their
parents.
And talking about the standard of living of our youth, I
want to say this to all the young people out there. I know
what you're up against if you left college with a ton of loans;
it's not enough just to make college more affordable. You
need help right now with the debt you already have. Well
work on that, from day one.
Your generation is the most tolerant and connected our
country has ever seen. It is our job to make sure that you
have the space, resources, and freedom to contribute to the
future of this nation. In the days ahead, we will propose new
ways for more young people to get involved in national serv-
ice. We also need political parties to be more welcoming to
your generation. We need more bright young minds at the
leadership of these parties or running for ofce. [...]Thatis
the energy and engagement we need to guarantee the pros-
perity of the United-States, so this country remains the best
in the world, for the many years to come.
This short excerpt of a political speech would make me
more likely to...
(1 = Not at all true and 5 = Completely true)
1. ...advocate for this candidate.
2. ...vote for this candidate.
3. ...talk to my friends, neighbors, family, and colleagues
in favor of this candidate.
4. ...give money to this candidates campaign.
5. ...join this candidates campaign.
6. ...do everything I can to get this candidate elected.
7. ...advocate against this candidate (r).
8. ...vote against this candidate (r).
9. ...talk to my friends, neighbors, family, and colleagues
against this candidate (r).
10. ...give money to the campaign of an opponent to this
candidate (r).
11. ...join the campaign of an opponent to this candidate (r).
12. ...do my best to ensure that this candidate does not get
elected (r).
Received November 17, 2019
Revision received January 6, 2021
Accepted February 2, 2021 n
22 FRANCIOLI AND NORTH
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... The WHO (2021) report on ageism defines older adults as 60 years and older, although it is recognized that age is a social construct (Giles & Reid, 2005, S.R. . Ageism exists toward groups across the age continuum, such as young adults who face negative stereotypes (entitled, reckless, spoiled, unqualified, unreliable, and unstable) and discrimination in employment, housing, and everyday life (also referred to as youngism; Ayalon, 2013;Bratt et al., 2018;Chasteen et al., 2020;Francioli & North, 2021;WHO, 2021). A focus on the important social issues of ageism toward the full range of age groups is beyond the scope of this article. ...
... For example, there is little research examining children's views of older adults (Flamion et al., 2020;Montepare & Zebrowitz, 2002), which could give insight on the formation of ageist stereotypes early in life and investigate how exposure to older adults such as grandparents impact these views among young children. Since ageism affects other age groups along the age continuum (Bratt et al., 2020;Chasteen et al., 2020;Francioli & North, 2021), it is also important to expand with a (2) consideration of the ageism experienced by different age perceivers , and likewise, (3) a consideration of the broader context that ageism is intertwined with intergenerational interactions of different age interactants . ...
Article
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Ageism is a worldwide crisis. The COVID‐19 pandemic exacerbated ageism toward older adults with hate speech, intergenerational resentment, and human rights violations. This article provides an overview of the interdisciplinary and international theoretical and applied research literature in three subareas: intergenerational attitudes and relations, psychological and physical effects of ageism on older adults, and reducing ageism. Cross‐cutting themes are the need to (1) consider positive (including seemingly “positive”) and negative views, treatment, and experiences of older adults, (2) expand the study of diverse populations including by age and country as well as intersectionality of ageism and other isms (e.g., ableism, classism, heterosexism, racism, sexism), (3) expand the study of the wide‐ranging manifestations of ageism at multiple levels of analysis including greater attention to human rights and new indicators of ageism, and (4) expand the circle of interdisciplinary and international collaborations within and across communities worldwide with all stakeholders and policymakers. Ageism and other isms are intertwined with and multiplied by population aging and other societal issues such as pandemics and climate crises. This article aims to further sound the alarm for the urgent need for age‐friendly societies and addressing ageism through basic research, preventive measures, and intervention efforts.
... Such focus, although undoubtedly important, led researchers to overlook the possibility that younger adults may also be target of stereotypes, prejudice, and discrimination due to their age (but see, e.g., Bratt et al., 2018;de Paula Couto et al., 2021). Aiming to fill this gap, a recent study by Francioli and North (2021) provided empirical evidence that not only older adults are target of age stereotypes and ageism, but that people also hold negative attitudes toward younger adults (i.e., youngism). Of most interest for our study, however, is that descriptive age stereotypes about older and younger people were found to be marked by distinct content, which was shown to depend on specific life stages (i.e., the content of age stereotypes change during the life span; Francioli and North, 2021). ...
... Aiming to fill this gap, a recent study by Francioli and North (2021) provided empirical evidence that not only older adults are target of age stereotypes and ageism, but that people also hold negative attitudes toward younger adults (i.e., youngism). Of most interest for our study, however, is that descriptive age stereotypes about older and younger people were found to be marked by distinct content, which was shown to depend on specific life stages (i.e., the content of age stereotypes change during the life span; Francioli and North, 2021). With