ThesisPDF Available

Spoken language: UK attitudes towards people who speak a different language to English.

Authors:

Abstract

Within the UK, a variety of languages other than English can be heard which is ever increasing with the rise of immigration (Jivraj, 2012; Lessard-Phillips, 2015). Fears of terrorism, with immigration have led to strong opinions towards other languages (Willgress, 2015), meaning attitudes towards different languages other than English, heard within the UK would be examined to determine if only language influenced a persons’ attitude towards groups of people who spoke that language. Using a cross-sectional design, an online quantitative study utilised ‘Bipolar attitude’ and ‘Feeling-led’ Semantic Differential Scales to record 98 participants’ responses in order to measure the positive and negative attitudes towards the language heard. A three-way mixed ANOVA was used to report whether attitude scores changed between participants for the different languages and whether gender was a contributing factor. Results indicated that where male and female participants’ attitudes were significantly similar, speaker gender did influence attitude scores without awareness of sentence context. Furthermore, Arabic did yield the lowest, most negative attitude score, whilst Portuguese, the highest, most positive attitude score, above English. Additionally, EU languages presented with a higher, more positive attitude average score than non-EU languages although English was not rated higher than Portuguese. Results further indicated truth in the hypothesis that attitudes to language differed depending on the language heard; as participants positively or negatively prejudge a group of people purely on the language they hear. Findings concluded there was a need for the UK to expand their acceptance of other languages, especially non-EU languages and embrace cultural and linguistic integration. Findings are to be presented to the UK Government and recommended for use to promote cultural diversity and awareness within the UK and through schemes to
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
Spoken language: UK attitudes towards people who speak a different language to English.
Mark A. Whittington-Buckley
Dissertation Research Project submitted in Partial Fulfilment
of the requirements for the Degree of
Master of Science
Psychology
University of Liverpool online.
22nd December 2016
i
Declaration
No portion of this work has been submitted in support of an application, for degree or
qualification of this or any other university or institute of learning.
Mark A. Whittington-Buckley
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
ii
Abstract
Within the UK, a variety of languages other than English can be heard which is ever
increasing with the rise of immigration (Jivraj, 2012; Lessard-Phillips, 2015). Fears of
terrorism, with immigration have led to strong opinions towards other languages (Willgress,
2015), meaning attitudes towards different languages other than English, heard within the UK
would be examined to determine if only language influenced a persons’ attitude towards
groups of people who spoke that language. Using a cross-sectional design, an online
quantitative study utilised ‘Bipolar attitude’ and ‘Feeling-led’ Semantic Differential Scales to
record 98 participants’ responses in order to measure the positive and negative attitudes
towards the language heard. A three-way mixed ANOVA was used to report whether attitude
scores changed between participants for the different languages and whether gender was a
contributing factor. Results indicated that where male and female participants’ attitudes were
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
significantly similar, speaker gender did influence attitude scores without awareness of
sentence context. Furthermore, Arabic did yield the lowest, most negative attitude score,
whilst Portuguese, the highest, most positive attitude score, above English. Additionally, EU
languages presented with a higher, more positive attitude average score than non-EU
languages although English was not rated higher than Portuguese. Results further indicated
truth in the hypothesis that attitudes to language differed depending on the language heard; as
participants positively or negatively prejudge a group of people purely on the language they
hear. Findings concluded there was a need for the UK to expand their acceptance of other
languages, especially non-EU languages and embrace cultural and linguistic integration.
Findings are to be presented to the UK Government and recommended for use to promote
cultural diversity and awareness within the UK and through schemes to
iii
educate the British-born UK population into accepting and not prejudging other languages.
Keywords: attitudes, language, quantitative, culture, gender
Word count: 300 (Abstract);
9979 (Main: excluding figures, tables, headings, ‘stand-alone text boxes’,
appendices, reference citations, and reference list)
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
iv
Acknowledgements
Formal thank you to Dr Stamatis Elntib for being my Dissertation Advisor and supporting
professional throughout this process.
Thank you to Dr Akhtar Wallymahmed for his initial guidance and integral role in the
acceptance of my proposal.
Thanks are also gratefully passed out to the anonymous twelve individuals who provided the
native voices which without, my research could not have taken place.
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
v
List of Abbreviations
RP Received Pronunciation
N Number of participants
ONS Office of National Statistics
ComRes Communicate Research Ltd
IV Independent Variable
DV Dependent Variable
VGT Verbal Guise Technique
UK United Kingdom
SDLS Semantic Differential Likert Scale
SDS Semantic Differential Scale
ANOVA Analysis of Variance
h0 null hypothesis
h1 alternative hypothesis
SD Standard Deviation
M Mean
pSignificance of probability
F Significance of variance
Sig. Significance
η 2Eta Squared
vi
TABLE OF CONTENTS
Table of Contents.…………………………………………………………………. vii
List of tables………………………………………………………………………... viii
List of figures………………………………………………………………………. ix
Introduction and background (not headed)……………...…………………………. 1
Literature Review…………………………………………………………………... 4
Methods……………………………………………………………………………. 14
Design………………………………………………………. 14
Participants and Sample-size calculation…………………… 15
Inclusion Criteria……………………………………………. 15
Exclusion Criteria…………………………………………… 16
Materials…………………………………………………….. 16
Procedure…………………………………………………… 19
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
Stimuli participants’ recruitment………….…... 19
Response participants’ recruitment……………. 20
Analysis………………………………………………………. 22
Results………………………………………………………………………………. 24
Discussion…………………………………………………………………………… 29
Limitations…………………………………………………… 34
Positive change…………………………..……. 35
Conclusion and Recommendations…..…………………………………………….. 36
Conclusion…………………………………………………… 36
Recommendations for future studies………………………… 37
References………………………………………………………………………….. 38
Appendices…………………………………………………………………………. 48
Appendix A: Study questionnaire design……………………. 48
Appendix B: Supporting tables (detailed on page viii) …… 49
Appendix C: Study Proposal…..…………….………………. 52
vii
List of tables
Table 1 Attitude Means for each language as a function of
gender……………………………….…………………………………... 25
Table 2 Levene’s Test of Equality of Error Variances ………..……………...… 27
Table 3 Comparison of attitudes towards EU vs Non-EU Languages….………. 28
Table 4a Positivity/negativity towards language……………………………….… 49
Table 4b Order of attitudes for female and male participants by language and
speaker gender……………………………………..…………………… 49
Table 4c Female vs male participant comparison: Attitude means for each
language and total scores…..…………………………………………… 50
Table 4d Female vs male participant comparison and total scores: Attitude
means for each language by speaker gender…………………………… 50
Running Head: SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO
SPEAK A DIFFERENT LANGUAGE TO ENGLISH.
viii
List of figures
Figure a. Total Means of attitudes towards Languages by Speaker Gender……… 26
Figure b. Comparison of EU and non-EU languages with English, by participant
gender….……………….…………………………………………..…… 29
ix
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 8
Spoken language: UK attitudes towards people who speak a different language to English.
Spoken language is not only a tool of communication spanning across cultures and
nations (Weitzman, 2013); but may also act as a barrier through misinterpretation of sentence
context and attitude. Allowing prior experience and media to distort perceptions of a
particular individual and assigning stereotypes to groups of people, could give rise to forming
attitudes towards these groups, based on the difficulties of interpreting and guessing their
language context without actually knowing what is being said (Adler, 1991; UKEssays,
2015). To fuel people in assigning attitudes to spoken language, recent terrorist events in
Europe have become widely reported, resulting in fear-led opinions (Willgress, 2015). With
sixty-five reported incidents in Europe involving injury or death since the start of 2015; six
were in the UK (TheReligionofPeace, 2016). Furthermore, ever present media reported
threats made towards countries such as the UK by Muslim extremists, highlights the current
fear and hesitant acceptance of languages such as Arabic due to the feeling that accompanies
the language, a feeling manipulated by the leave campaign for ‘Brexit’ offering that
‘massacre’ attacks could hit the UK if Britain was to remain in the EU (Robertson, 2016);
words which could have aided their vote to leave the EU. With such regular reports sparking
fear in the UK and USA public, languages such as Arabic, increase suspicion upon simply
hearing the language (Willgress, 2015); as the context is unknown. Furthermore, with the UK
voting to leave Europe, Siegel (2016) and Donnella (2016) argue this by some was motivated
by their fear of both European and non-European immigrants coming to the UK. Additionally
the British Social Attitudes report (Park, Bryson & Curtice, 2014) argue not speaking English
is a lack of ‘Britishness’ with results determining the majority of study participants feel
Britain does not want European or non-European immigrants and should be more ‘Britain
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 9
focussed’ with 95% arguing speaking English is what makes you ‘truly British’. With this in
mind, it would be assumed that attitudes towards other languages would be predominantly
negative, especially as the UK is a diverse country linguistically (McDonagh, 2010).
However, with a variety of languages spoken within the United Kingdom; diversity
awareness means understanding attitudes towards different languages can help promote a
positive outlook to other groups who speak a language other than English. Wolfram (1998)
argues there are three parts making up ‘awareness of a language’s impact on people’, one
being consciously aware of ones’ own attitude towards a language, thus if a person can be
aware of their attitude, they could perhaps mould their own thoughts to include acceptance of
other languages.
With the level of ethnic minorities increasing within the UK (Jivraj, 2012; Lessard-
Phillips, 2015), it is likely UK nationals will experience hearing a rising number of languages
other than English spoken within the UK. The purpose of this study is to explore how UK
nationals feel towards and make judgements on non-English speaking groups of people based
only on the spoken language they hear in order to better understand typical attitudes shown
towards non-English speaking groups. Meadows (2009) argued, people typically visualise
what they feel a person is like when they hear them speak their language, allowing a personal
feeling and opinion to form which may depict their attitude towards that person, and in-turn
the group who speak that language. However, as the current study will not include a visual
image to accompany the language, participants will be left to form their own inner opinions.
To remain current, using languages deemed to be most important to the UK’s future
(Tinsley & Board, 2014); most common languages heard in the region of the lead researcher
being English, Portuguese and Polish (Norfolk County Council, 2015), as well as those
highlighted negatively in the media; the languages chosen were Arabic, Chinese, Portuguese,
Polish, Punjabi and English. Xia (2013) discusses influences of gender on attitudes as
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 10
females take the effects of the words they use and hear into consideration, more than males,
paying more attention to the rules and impact of language, thus gender is also assessed to
determine if speaker or participant gender influences responses. Furthermore, recording the
age of participants can perhaps indicate a trend in whether age influences a particular attitude
towards a language. Thus, understanding the inclination of British attitudes towards non-
English languages and whether their judgement is influenced by the words they hear is
important in order to aid and implement strategies within local and national governments in
the UK. This can assist the promotion of multi-lingual diversity, awareness, tolerance as well
as acceptance within the UK. This in-turn could help social integration within an entire
nations’ mix of societies, such as the UK (Kouassi, 2016). Without such acceptance, current
increasing negative attitudes such as racist thoughts and comments, and even physical
violence (Smith, 2016) towards the afore mentioned non-English speaking groups, could
become aggravated (Taylor & Muir, 2014).
Therefore, the aim of this study is to explore the attitudes of UK nationals toward
non-English speaking groups with the UK to see if there is a trend of specific attitudes
towards certain languages heard which would affect the wider group of people who use the
same language within the UK. Furthermore, comparing EU languages with non-EU
languages can provide information about UK attitudes towards such two groups on differing
continents.
With this in mind; the objectives for this research are:
To measure the attitudes of UK nationals towards different spoken languages
To assess gender and age effects of speaker and response participant on UK nationals’
attitudes towards non-English and English speakers.
To investigate attitude differences as a function of the five non-English languages, and
English language spoken.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 11
Furthermore to test whether spoken language does or does not affect UK nationals’
attitudes towards a particular group of speakers, the main research question is:
“Do foreign spoken languages influence UK nationals’ attitudes towards non-English
speaking groups?”
The hypotheses for this study would be as follows:
H0: The attitudes of UK nationals towards groups of non-English speakers will not
differ as a function of the language under assessment.
H1: The attitudes of UK nationals towards groups of non-English speakers will differ
positively or negatively as a function of the language under assessment.
Literature Review
With attitudes to spoken language being the focus, reviewing literature highlighted the
limited amount of previous studies involving attitudes towards groups of people within the
UK whose first language is not English. Mehmedbegovic (2008) discussed how sixty years
ago, all languages except English were prohibited in schools in the UK, thus not many non-
English languages were widely heard until more recently. Therefore, to support the aim of the
current study, in an attempt to improve acceptance, government officials such as Baroness
Hooper (Mehmedbegovic, 2008), argued that promoting the use of other languages assists
young people in recognising, accepting; and further promoting other languages within their
community, allowing them to thrive in cultural diversity and acknowledge multilingualism in
their futures.
With negative attitudes felt in recent media towards speakers of non-English
languages, implying using different languages can cause barriers to social integration in the
UK (Buckley, 2012); Marshall (2013) argued how different UK accents have also hindered
certain groups of people in their future success. Using a survey of ten UK cities/accents by
ComRes in London, Marshall (2013) showed that 28% of the UK population felt
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 12
discriminated against due to their accent, as a result of negative attitudes from UK
participants towards them. Findings indicated that the Devon accent in southwest England
was voted as the most friendly, whilst Liverpool was voted as most unfriendly. Marshall
(2013) further noted how UK populations’ accent affected peoples’ view of what level of
intelligence a person has, indicating that the ‘Queen’s English’ was most intelligent sounding
but Liverpool was the least intelligent sounding. This in-turn affected participants’ perception
of trust-worthiness, results showing those speaking Queen’s English were most trustworthy
with those from Liverpool being least trustworthy (Marshall, 2013). Therefore, if UK citizens
were keen to assign attitudes towards differing variations of their own language, perhaps they
would be as liberal with their attitudes towards languages different to their own.
Prior to this, Clark and Schleef (2010) had examined attitudes of native English
speakers towards 34 UK accents to include Glaswegian, Edinburgh, Indian English, Welsh
and the Birmingham accent, using a ‘pleasantness scale’. Results showed the Scottish, Irish
Northeast and Afro-Caribbean English were rated as the most pleasant to listen to.
Researchers however noted the Birmingham accent as least attractive and where ‘Queen’s
English’ (RP) accent was rated most prestigious, it was also seen as unattractive despite being
voted most friendly, intelligent and most trustworthy by Marshall (2013)’s study.
Furthermore, Clark and Schleef (2010) discovered that female voices were deemed more
pleasant than male’s in general, which the current study would also examine, to see if a
particular trend of attitude was different or similar between males and females. Prior to this,
Long and Preston (2002) had undertaken studies to determine if Dutch people offered
different attitudes towards their own dialects and other languages. Examining the aesthetics
of the Dutch language, the authors used 45 child and 42 adult participants of mixed gender
across the nation, to listen to four speakers using four different dialects. Their findings noting
the standard accent as more beautiful than the other dialects. However, using only female
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 13
speakers meant no gender differences could be noted. Their second study used 30 male
speakers and 113 participants of mixed age and gender. Once more standard dialect was
found to be more beautiful yet context was key to their results, which is what the current
study aimed to avoid, concentrating on simply the language. Long and Preston’s third study
involved attitudes to eight other languages within Europe. However, although results did offer
differing attitudes, with Russian seen as the most ugly, American English and German as the
most loud, offering a negative attitude (Long & Preston, 2002); these were still based
aesthetically which the current study did not measure, by using voices which were native, yet
emotionless. Further to this, Clark and Schleef (2010) noted that loyalty amongst specific
regions had an effect on a significant number of choices. This means that participants from
Scotland rated ‘Scottish English’ as more prestigious than other regional variants of English,
such as London, Newcastle, or Birmingham; indicating they only rated ‘Scottish-English’
better because they themselves were Scottish; a finding which mirrored Long and Preston
(2002). Therefore, perhaps the participants of the current study, being UK-born would rate
English with the most positive attitude, as they would perhaps be biased towards English.
One significant limitation with this study was its small sample size, using a sample of just
thirty seven people (N=37) meaning it was difficult to generalise the results to represent an
entire population. Taking Clark and Schleef (2010)’s small sample size into consideration, the
current study proposed to significantly increase the sample used, to improve validation of
results. With the final number of participants totalling 98, being almost three times more than
Clark and Schleef. Moreover in light of current increased immigration within the UK (ONS,
2016), the current study will observe common non-English languages heard in the UK rather
than simply UK accents, although this study highlights that UK born people still feel able to
register an attitude towards the way another person speaks. Queen’s English accent will be
used in the current study, as a control.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 14
One advantage of Marshall (2013)’s research was that using ComRes’ qualitative
approach saw them interviewing 6,045 participants, weighting their data to represent the
national opinion of all adults in the UK and with a much greater participant number yielding
a more accurate representation of the UK population than Clark and Schleef (2010). A further
observation of Marshall (2013) noted how 80% of UK employers admitted to allowing
regional accents to influence their decisions within the workplace, confirming in this instance
that UK employers allowed themselves to adopt a negative attitude towards an
employee/interviewee if they did not like their accent, meaning spoken language did affect
their attitude towards a particular group of people and if opinions towards an accent
influenced employment, then perhaps language was considered too. This finding is what
inspired the current study to determine if there is a trend in certain attitudes being shown
towards a particular language.
However, attitudes within the workplace were not just limited to employer decisions.
Tenzer and Pudelko (2015) and Zhang (2010) examined barriers amongst peers at work and
within society, similar to that of the current study in observing attitudes to other languages in
the social environment. Tenzer and Pudelko (2015) conducted qualitative interviews with
multinational teams who have culturally diverse members and how the professional
relationships influenced language barriers which in-turn affected the workplace. With an aim
to better understand the conversation as a whole and the problems different languages brings,
researchers noted how conversational context was misunderstood amongst people from
different nations which caused difficulties when they translated conversations into their own
language. This was made more difficult when certain cultural expressions were used, which
were only relevant to a particular culture, thus context was seen as important. Zhang (2010)
however used quantitative questionnaires, incorporating a 5 point Likert scale, similar to the
current study. Their focus was more on peer rejection and exclusion in an American society
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 15
whereas Tenzer and Pudelko (2015) argued that working alliances could be damaged by
workplace barriers through an increase in stress, embarrassment and anger, leading to a
decreased ability to solve work-based problems and upset the smooth running of a business
through the unwillingness to help colleagues and measures to overcome such problems. It
was noted that perhaps if language barriers were not a factor of differing cultures/races in the
workplace, the problems of peer rejection and misunderstanding of each other may not exist.
In support, Kulkarni and Sommer (2014) argued that linguistic diversity within Indian
workplaces negatively affected working relationships by causing exclusion amongst
colleagues, thus negative attitudes towards other languages caused barriers in that
community. Their theoretical paper examined colleagues at work and found that due to
feeling less accepted by peers led to poor diligence, however without the support of empirical
evidence, this statement is difficult to quantify. Furthermore Dotan-Eliaz, Sommer and Rubin
(2009) added that peer exclusion as a result of working language barriers were more likely to
increase anger, reduce group adhesion, increase indolence and aid the deterioration of
relationships in the workplace. This was further supported by Tenzer and Pudelko (2015) who
also found that language barriers led to poor work productivity through performance being
affected and multinational organisations were adversely affected. It was suggested that such
issues could be avoided if management ‘embraced’ linguistic diversity in the workplace
instead of allowing it to be a negative aspect of the work environment. The current study
would support this as its findings will be presented to the local and national government in
the UK to aid schemes for educating the UK public in linguistic diversity and acceptance.
One limitation of Tenzer and Pudelko’s study however was how thematic coding analysis was
recognised as making the data difficult to quantify and compare.
In attempts to determine where a speaker came from, McKenzie (2015); continuing
the work of Clopper and Pisoni (2007) looked at whether participants could determine a
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 16
speaker’s origin within the US, based on their spoken accent. Task-led surveys found
participants who had previous personal knowledge of a particular regional dialect showed
greater detection of that dialect, meaning ‘prior experience’ was an influential factor.
However, perhaps if their prior experience was negative, this could affect their attitude
towards the people who spoke the language; although this was not measured. McKenzie
(2015) focused on how UK nationals used a person’s language and accent to identify their
origin within the USA, finding, like Clopper and Pisoni (2007) that ‘vowel sounds’
influenced correct interpretation of a speaker’s origin. Using six speakers, McKenzie’s
research was biased towards one particular continent, as three speakers were from East-Asian
countries; one West Indian, and two from the UK. Results did show a significant number of
participants correctly nominating a languages’ origin, however their findings were limited by
not investigating whether participants had positive or negative attitudes towards the speakers
of the languages, based on their voices, which the current study will address.
Zhang (2010)’s study did examine a wider field of attitudes to languages heard using
interviews to discover how people communicated effectively and created new relationships
with people. With the current study noting attitudes to spoken languages, those attitudes
create stereotypes which effect negative thoughts in people (Forbes & Schmader, 2010).
Zhang (2010) focused on Asian Americans arguing that they were poorly represented within
the TV industry creating negative images of those groups of people. Zhang (2010) felt this
was due to Americans creating negative stereotypes which were media-led, such as TV
programmes implying Asian people were ‘nerd-like, passive and quiet’. However, Zhang also
offered that Asian people preferred to use their own language rather than English. Where this
may be simpler for those whose first language is not English, Endley (2014) reports how a
UK based company advised Polish workers they may lose their jobs if they did not speak
English at work, as it aids a better working environment. Perhaps this contributes to the
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 17
hypothesis that attitudes to languages do differ, although perhaps this was focused on all
languages which were not English and not just ‘Polish’. Zhang (2010) using 169 students
from a varied ethnic background, conducted a study which indicated that media-led
perceptions predicted Asian Americans would have poorer communication and language
skills than white American’s. Results supported the media expectations as researchers
reported that Asian (Chinese) Americans were more likely to be excluded by peers and be
less likely to form friendships, experiencing negative questioning such as “Do you speak
English?” And “Where are you really from?” (Cheryan & Monin, 2005). Furthermore,
American attitudes towards Asian-Americans stereotyped them as ‘evil’ and ‘untrustworthy’
leading to hate crime towards Asians, which in-turn meant Asians suffered discrimination and
rejection by many US nationals (Kawai, 2005). To eliminate the risk of stereotyping certain
races, the current study adopted a method which examined only the language thus groups of
people could not be discriminated against based on their ethnicity. One limitation which
Zhang did highlight was that the sample were predominantly white, middle class American
students, who perhaps succumbed to media-stereotyping (Zhang, 2010, 2015). However, the
current study was open to all UK-born citizens, between the age of 18 and 80 to ensure a
mixed view across all social, age and gender groups. Furthermore, the scenarios used by
Zhang (2010) were hypothetical and thus unrealistic; with no explanation as to why
participants attitudes agreed with media perceptions being given due to quantitative surveys
being used over qualitative interviews.
Another aspect of positive and negative attitudes that hold importance in the current
study, was shown by Kite and Whitley Jr (2012) who focussed their research on the positive
and negative attitudes within stereotypical ‘English’ phrases used by UK nationals. Phrases
such as ‘excuse my French’, ‘Indian giver’, ‘get off scot free’ use another nation within the
phrase and was observed as being predominantly negative in its context, which in-turn was
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 18
argued could inadvertently plant negativity into people about the nation involved. For
example, it was argued that perhaps ‘Indian Giver’ meaning a person gives, but then takes
back is a negative action and could influence negativity towards Indian people because of the
phrase, through cultural traditions, misunderstood (Goodwyn, 1967). Results from Kite and
Whitley Jr’s small sample of 34 social psychology students supported this by showing how
participants became more self-aware of their use of these phrases in a negative context which
translated into negative attitudes towards the groups of people who were referred to in the
phrase, due mostly to them describing a person’s behaviour negatively. Researchers found
that people generally thought negatively towards Indian people as fickle and insincere in their
generosity, through the term ‘Indian giver’ (Kite & Whitley Jr, 2012). Where the current
study used one generic group of sentences with no weighted context towards any particular
group of people, Kite and Whitley Jr’s findings show that their awareness of their negative
attitudes became apparent to themselves, supporting the need for education of linguistic
awareness for the current study findings. However, their small sample of psychology students
could create unconscious bias (Shire Professional, 2010) and could not be generalised for a
wider population; again overcome by the current study being open to people from any
educational background aged eighteen to eighty, to allow a more diverse and real world
opinion.
An example of where negativity does affect attitudes towards groups of people comes
from Dicker (2003). Despite positive results, some previous research has led to negative
attitudes becoming prevalent for example how a certain amount of the American population
judge a persons’ ‘intelligence’ based on their voice, such as judging Latin Americans, who
use the Spanish language, as having ‘low intelligence’. This can affect both Mexican and
Spanish people, who both speak the same language, affectively applying the same attitude to
both nations (Dicker, 2003), simply by their spoken language. Therefore, participants within
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 19
the current study could be negatively influenced by personal bias of a language they hear,
based on stereotypes, or prior experience of the language and people who speak it.
With the current study assessing positive and negative attitudes towards other
languages, a similar language attitude study was conducted by Ibarraran, Lasagabaster and
Sierra (2008), in Basque Country between France and Spain; examining attitudes to other
languages heard in a school setting. The authors noted that 57.6% of the 125 non-Basque
students in their research, were immigrants. Although attitudes towards the different
languages were both negative and positive, researchers found that where attitudes towards
Basque were predominantly negative and immigrants preferred to use the wider-used Spanish
language over Basque to mix well with the majority of the population, in support of Buckley
(2012); although English was favoured the most, second only to their native language of their
home country which contradicts their previous finding of wanting to use Spanish in order to
mix well with the larger population. Researchers discovered than participants attitudes
towards using their home language was most favourable, followed by the wider-used Spanish
language, then English, with the country’s home language of Basque being unfavourable.
Therefore, in the current study, perhaps participants will adopt a negative attitude towards
other languages except English, being their home language. Limitations of this study were
that with 48% of the non-Basque population being Latin American and the questionnaire used
was in Spanish, perhaps significant bias in favour of the Spanish language was displayed
meaning results were not a true representation of attitudes. This was acknowledged by the
researchers who advised that results should be “considered with caution” (Ibarraran,
Lasagabaster & Sierra, 2008). Furthermore, as only students were used of a similar age, it
only measured one age group, whereas the current study will allow all ages to offer opinions
which can be gathered by different generations. Ibarraran, Lasagabaster and Sierra (2008),
used a reliable questionnaire, previously used by Baker (1992) to discuss the importance of
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 20
multi-linguistics; and their quantitative study used a 10 item Likert scale. Findings suggested
that despite the Spanish bias, attitudes towards ‘Basque’ were negative for both Spanish and
non-Spanish speakers, and positive for both Spanish and English, indicating language
awareness was required within the country’s education curriculum. This supports the concept
that findings from the current study can be used to assist government linguistic awareness
schemes within the UK.
Therefore if negativity was a factor of hearing other languages, perhaps the results of
the current study will indicate this also; or perhaps quantitative research will offer no support
of this. The current study would look to discover if attitudes to other languages were mostly
positive, negative or not affected by what the language was based on the speakers voice. Yet
with an increasing presence of non-English languages in the UK (Chapman, 2014), perhaps
the findings could help reduce prejudice towards groups of people based on their spoken
language by showing that if speech with context unknown does influence an attitude towards
a particular group of people, creating awareness may help schemes to promote acceptance of
linguistic diversity.
Methods
Design
Using a cross-sectional research design consisting of participants registering their
attitudes towards each language, with no follow-up required; an online quantitative
questionnaire was used for the study. Using language spoken as the ‘Independent Variable’
(IV) with six levels (languages); and attitudes as the ‘Dependent Variable’ (DV); the attitude
choice’s, frequency was measured as a single occurrence for each participant in the study.
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DIFFERENT LANGUAGE TO ENGLISH. 21
When deciding the language speakers for the stimuli, difficulty in finding an
individual speaker who could offer fluency and natural speech for each language would prove
extremely time consuming and difficult. To ensure authenticity and fluency, twelve individual
native speakers, six male and six female were sought thus ‘Verbal Guise Technique’ (VGT)
was used.
Tinsley and Board (2014) reported UK’s important languages for the future, their top
ten list of the languages chosen as being currently heard within the UK which included three
used in the current study, being Arabic, Portuguese and Chinese. Out of the remaining
languages within their list, 6 out of the 7 were European but were not chosen for this study as
many European languages are instantly recognisable with several words similar to English
with a variety of French, German, Italian, Greek, Scandinavian regions’ words forming the
English language historically (McCrum, Cran & MacNeil, 2002); meaning the sentence
context might be easier to comprehend. Furthermore, these languages such as French,
Spanish and German being recognisable through being taught in UK education (Tinsley &
Board, 2014), may result in participants already having ingrained opinions and attitudes
towards them, encouraging biased responses. Therefore, using languages such as Arabic,
Punjabi, Portuguese, Polish and Chinese which were still common to be heard within the UK
(Tinsley & Board, 2014), but not so recognisable meant attitudes were more likely to be
attributed to the language and not the context.
Participants and Sample-size calculation
In order to gain a sample of the UK born population, the survey was open online to
encourage a UK wide range of participants. Using a calculation through ‘Statcal-EpiINFO
version 7.1’ the following formula (1.96 2*p(1-p))/e2 was used to calculate an appropriate
sample size for this study to offer significant results which can be generalized for the UK-
born population.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 22
To encourage a wide range of ages, personalities and backgrounds, the participants
were from the general UK-born public consisting of 98 individuals (Mean Age = 40.95, SD =
14.38). 46 were female (46.9%) and 52 were male (53.1%). With no current existing data, a
‘p’ value of 0.5 (50%) was set (p = 0.5) and an ‘e’ value was set to 0.05 (5%). This meant the
required number of participants was 384, rounded to 400 with a view to equally distribute the
results by age and gender, so long as all 400 were collated. With a response rate of 24.5%
(98/400); this number of British-born participants sought were a significant representation of
the population based on the east coast of England, where the results of the study will be
presented to the local government, where its constituents were made-up of 93.5% UK born
and 6.5% non-UK born population (Qpzm, 2012).
Inclusion Criteria
To ensure the study undertook to measure attitudes of UK born citizens towards non-
English languages, criteria for inclusion asked participants to be UK-born, British males and
females aged between 18 and 80, with English as their only, or main language. Use of the
term ‘Main’ implies those who are born in the UK but who are also able to speak another
typically secondary school-learnt second language i.e. French, German or Spanish.
Exclusion Criteria
Participants who may hold UK citizen status but who were not born in the UK, thus
considered to be an ethnic minority with a main language other than English were excluded
from the study as the likelihood of their attitude to languages other than English being more
positive is higher, as well as the likelihood of understanding the study stimuli languages is
also greater due to their wider language exposure. Therefore, anyone UK-born who has a
main language other than English, due to their heritage, or culture were also excluded.
Materials
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DIFFERENT LANGUAGE TO ENGLISH. 23
The survey questionnaire overall contained twelve parts, with six male voices and six
female voices, correspondingly speaking different languages, including English. Two separate
Semantic Differential Scales (SDS) were used for each Language/voice (Appendix A); 1 scale
contained five bi-polar likert scale responses and the second scale contained two likert scale
questions. Thus, a total of seven questions were asked for each voice/language heard. Heise
(1970) argued that SDS scales were a valid measurement of attitudes which were used by
Nickols and Shaw (1964) in a study to measure attitudes towards professors at college; and
the idea of ‘the Church’ and the attitudes towards it; acknowledging the method to show
validity. Ajani and Stork (2013) also used a 10-item questionnaire with bipolar adjectives to
gather information on attitudes towards new technologies, noting the SDS method to be easy
and a reliable way to quantify the results. With the purpose to determine the ‘attitude scores’
(Dependent Variable – (DV) towards the voice/language they hear in the current study,
participants used the online form to register their score between 1 and 5. The scoring
structure was calculated through SPSS using an average score for all participants. Thus scores
between 1-1.99 = very negative attitude; 2-2.99 = negative attitude; 3 = Neutral/unsure; 3.01-
3.99 = positive attitude; 4-5 = very positive attitude. Participants attitude scores will denote
their attitude feeling towards the language they hear and unless all participants choose ‘3’, the
scores will either show as positive, or negative attitude. Therefore higher scores are more
positive, lower scores are more negative.
The two scales were Semantic Differential Likert Scales (SDLS) known as ‘SDLS1:
Bi-polar Attitude Scale’ and ‘SDLS 2: Feeling-led Attitude Scale’ with the data being
collected through ‘Qualtrics’ (example can be viewed in Appendix A). SDLS 1 utilised a
Semantic Differential ‘Likert’ Scale with 5 sets of bipolar (opposite) adjectives.
Participants registered their attitudes to each voice using SDLS 1 “Bi-polar Attitude
Scale” through a bi-polar adjective scale (Osgood et al., 1957). Aligned with Ajani and Stork
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 24
(2013), the methods for scoring each item were to be added into a total score and divided by
the number of items (5) which would give the participants individual score. Ajani and Stork
(2013) proved effective use of this method with a reliability rating of 0.85, indicating a ‘good’
rate of reliability for the use of ‘SDS’. According to Cronbach’s Alpha (Cronbach, 1951;
Santos, 1999; Nunnally, 1978); a reliability score of more than 0.70, is classed as ‘acceptable’
thus a good ‘rate of reliability’.
The second scale used in the study questionnaire, SDLS 2 “Feeling-led Attitude
Scale” measured participants’ feelings towards the person they heard speaking consisting of
two questions, using a 5 point Likert scale running concurrently after the Semantic
Differential scale (SDLS1) for each voice in the questionnaire. With two opposing questions
(1 positive and 1 negative question) a score of ‘5’ for each question equates to a positive
response with ‘1’ equating to a negative response as the responses were reversed to keep the
scoring consistent. This was chosen as an easier method for scoring, rather than having to
reverse the scoring itself manually. Once more, in line with Ajani and Stork (2013), using a 5
point Likert scale (Likert, 1932), the individual item scores were added to form a total score,
then divided by the number of items, being ‘5’ giving an attitude score for each participant,
for each voice/language.
With initial uncertainty in using a 5-point or 7-point Likert scale for the current study,
it was noted that Preston and Colman (2000) argued a 7-point scale would yield a marginally
higher rate of reliability than a 5-point scale. However, Preston and Colman (2000) further
indicated that both 5 and 7 point Likert scales are more reliable than other Likert scales with
higher or lower points. Furthermore, although Finstad (2010) details how a 7-point Likert
scale tends to offer a more accurate representation of the true feelings of a participant; both 5
or 7 point scale are both acceptable forms of measurement. For the two simple questions in
‘SDLS2’ a 5-point scale would be more beneficial as the questions aim to encourage a
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 25
positive or negative response rather than a sliding scale of positivity or negativity, thus
anything more than a 5 point scale may be too difficult to score as the level of variety of
positivity and negativity would be over-necessary with too much variety. Total scores
indicated the number of participants registering a score between 1 and 5 adequately
displaying their attitude towards each voice/language. Following this, a comparison was
made to show consistency of responses for participants.
To calculate TOTAL score for each part (scale), the sum of item scores for each part
(scale) were added together, for analysis. Jha, Bajracharya and Shankar (2013) used this
method successfully, deemed a reliable method in their research to better understand attitudes
to medicine before and after educational intervention meaning the necessity to conduct
analysis of each item separately was dismissed.
Procedure
With no ethical concerns to address, ethics approval was received 14th July 2016, with
no conditions attached. Therefore the study was able to be undertaken. Participants gave
consent by reading a statement and clicking a tick-box to show they understood the purpose
of the study, agreeing to participate and provide opinion before continuing, situation at the
beginning of the online questionnaire. Participants anonymity and confidentiality at all times
shall be assured with raw collected data only to be viewed by the researcher and dissertation
advisor and study data stored on a password protected computer, and kept for 5 years after the
study has ended. Raw data shall not be shared with any organisation.
In order to create a study where the voices/languages (Stimuli) could be heard and
participants could be found, it was necessary to create two separate adverts in order to attract
appropriate participants.
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DIFFERENT LANGUAGE TO ENGLISH. 26
Stimuli participants’ recruitment
Stimuli participants used for the production of the stimuli were recruited from a pool
of associates of the student researcher, using 12 native male and female speakers of the
required language to ensure authenticity of the language used. They were approached through
‘Facebook-friends’ and acquired through the participants recording their voices into a
recording device and emailing to the lead/student researcher. Following ethical approval, a
voluntary invite was sent to all potential stimuli participants. Participants were informed of
study’s purpose and requirements for the study with official permission verbally sought.
Upon acceptance of the proposal and ethics approval, male and female speakers were
recruited for their anonymous assistance.
Upon email agreement to continue and consent to use their voice for the study stimuli,
electronically signed; the speakers were asked to read four short sentences in their own
language:- Chinese, Punjabi, Polish, Portuguese, Arabic and English; both male and female,
using a recording device with no background noise. This stimuli collection method was
preferred and deemed to be most successful as the stimuli participants are already aware of
the Masters course undertaken through the facebook friendship circle and had previously
shown voluntary interest in providing assistance if required. Furthermore, this method
allowed the student researcher to ensure the same sentences were used for consistency, using
the same specific non-emotive sentences for all languages.
Each stimuli participant used were bilingual and fluent in both English and their own
native language, ensuring they were able to translate the required sentences required
accurately into their natural native spoken language.
The non-emotive sentence in question was “First you break an egg into a bowl. Then
mix with sugar and add some milk. After this, cover your baking tray with paper. Put the
ingredients on the tray and bake in the oven.”
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 27
The stimuli voices were uploaded to the survey questionnaire in ‘Qualtrics’ (Qualtrics,
2016). Each voice was played by the participants prior to answering the 7-item questionnaire
for each voice within the study.
Response participants’ recruitment
Research response participants were recruited through online advertising within social
media applications ‘Facebook’, ‘Twitter’ being the most popular applications amongst the
general population throughout the UK and most likely to attract a UK wide range of
participants; and the University of Liverpool Laureate community. Information given to the
potential participants within the advert include the study’s purpose, inclusion/exclusion
criteria, proposed outcome and contact details for further information.
Recruitment of participants was voluntary and continued for either 2 months, or until
the participant quota was filled. Due to limited timing and the difficulty in raising awareness
of the study through social media, university forums and communities; the study was ceased
by the lead researcher after 2 months. Valid responses were collated and totalled 98. Although
under the target sample size of 400, 98 was still an appropriate amount of participants to be
able to conduct analysis. Data was then collected through ‘Qualtrics’ (Qualtrics, 2016) which
hosted both the survey questionnaire and the twelve male and female stimuli voices, speaking
‘Chinese, Polish, Punjabi, Arabic, Portuguese and English’. These languages were chosen for
being those most likely to be heard in the UK according to the 2011 census. English was first
most likely, Polish second, Punjabi was third, Arabic was seventh but a very current language
to be heard and very prominent in the media at present. Chinese was ninth and an upcoming
language thriving to become dominant in the business world (Pak, 2012); as well as the
world’s number 1 language of the country with the highest world population, Portuguese was
tenth (Evans, 2013) and although a similar amount of people are in the UK from both Spain
and Portugal (Migration Watch UK, 2016) Portuguese was chosen over Spanish as it is more
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 28
likely to be heard in the UK than Spanish (Gopal and Matras, 2013), thus more likely to
invoke an attitude response from UK-born participants.
Participants were informed that answers provided would be confidential and with just
gender and age being used for statistical purposes. Prior to the questionnaire commencement,
a statement informed participants that by clicking the ‘tick-boxes’, they confirm they are UK-
born with a main language of English and agree to continue with the study, although they
have the right to withdraw at any time. They also agree that they understand how to conduct
the study and its purpose, giving consent that their responses would be used as part of the
study. For those agreed to continue, the survey continued and the participant information
sheet was available, together with contact information should participants need clarification
or assistance with the study.
Participants were informed that the survey should take approximately fifteen to
twenty minutes to complete and requested to record their responses on the form provided
through ‘Qualtrics’ with voices 1 – 12, corresponding with the relevant 7-item questionnaire.
The study was active online for 2 months from 15th July to 15th September 2016 and
data was collected anonymously, as no personal details were required by participants except
gender, age and acknowledgement of being UK-born with English as a main or only
language; through ‘Qualtrics’; and downloaded anonymously; although their name could be
provided if they wished.
Analysis
Using SPSS, a three-way mixed ANOVA will be used with repeated measures on
speaker gender (i.e. male/female); and language spoken (i.e. Chinese, Polish, Punjabi,
Portuguese, Arabic and English); plus between-subjects factor the response-participant
gender. It is also aimed to control for response-participant age by using ‘age’ as a covariate or
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 29
alternatively, depending on age distribution and final sample size, introduce age as an
additional ‘between-subjects’ IV.
In determining if different languages heard (IV) affects attitudes (DV), towards an
ethnic group; and whether gender of the person speaking that language makes a difference to
the attitude; the within-subject independent variables (IV) would be ‘language’; including 6
levels:- Chinese, Polish, Portuguese, Punjabi, Arabic and English. ‘Gender of speaker’ would
serve as the within-subject IV’s; and gender of response participants will be the between-
subject IV both having two levels, male/female.
With the results set to show if the null hypothesis (h0) or alternative hypothesis (h1)
are true, a marginal p value is appropriate at 0.05 (p = .05).
Using IBM SPSS Statistics Version 21, raw scores were converted to Z-scores, to
obtain standard deviation for the data. As the population size is over 30, a Z or T score can be
used, especially as the population SD (Standard Deviation) can be calculated, using the
formula
(Raw scores were added and divided by the amount of items to calculate the mean score for
each scale. Then the distance from each raw score to the mean will be calculated by adding
each score squared to gain the average which will equal the variance (average squared
distance to the mean). The square root of this figure will give the Standard Deviation
(Average distance to the mean).
To eliminate negative scores and without having to working with negative figures,
making the calculations easier to interpret, the Z-scores accumulated from the Semantic
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 30
Differential Scales, which have a mean of 0 and standard deviation of 1; will then be
converted to T-scores which have a mean of 50 and a standard deviation of 10. (T=50+10xZ).
From a report of 144 questionnaires started only 98 were completed, meaning 33% of
the questionnaires were incomplete. Therefore, those responses have not been included in the
analysis, nor the following results. From the responses, Initial Case Processing Summary
showed how many cases had missing values (female N=20; male N=18) although in total
53.1% were male (N=52) and 46.9% percent were female (N=46). For the purpose of the
results, 60 valid remaining cases (female N=26; male N=34) were used for analysis.
Results
A three-way mixed ANOVA with repeated measures on speaker gender (male/female)
and language spoken (Chinese, Punjabi, Portuguese, Arabic, Polish and English); was
performed on total scores to explore whether a particular language from the study sample
affected attitude scores towards it; and whether participant gender or speaker gender affected
attitudes.
The main effect of language violates the sphericity assumption (p < .05), thus
Greenhouse-Geisser correction is adopted at .590. There was a significant main effect of
language F(2.94, 171.02) = 28.07, p < .001, η2 = .326 . Further noted was that total scores
showed ‘Arabic’ yielding the most negative attitude mean (M) (M = 43.05, SD = 11.59); and
‘Portuguese’ the most positive attitude means (M = 56.38; SD = 8.75).
In comparing multivariates, to explain further the main effects of language and to
reduce the risk of Type 1 error, Post-hoc tests with a Bonferroni correction of .008 took place.
There was a statistical significant difference for English and Portuguese with all other
languages, Portuguese specifically displaying significantly higher attitude scores than
Chinese, Punjabi, Polish and Arabic. Portuguese with Arabic 6.61 (95% CI, 4.20, 9.02), p < .
001. With Polish 4.91 (95% CI, 2.95, 6.88), p < .001. With Chinese 4.51 (95% CI, 2.60,
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 31
6.42), p < .001. With Punjabi 5.70 (95% CI, 3.59, 7.81), p < .001. With English 2.26 (95%
CI, 0.29, 4.23), p = .013. Furthermore, significant difference was shown for Arabic with
Polish -6.61 (95% CI, -9.02, -4.20), p < .001; with Chinese -2.10 (95% CI, -4.08, -0.12), p = .
029; and with English -4.35 (95% CI, -7.12, -1.57), p < .001. Statistical significance was also
shown for Polish with English -2.65 (95% CI, -4.97, -0.33), p = .013. Additionally
significant differences was shown for Chinese with English -2.24 (95% CI, -4.49, -0.001), p =
.05; as well as Punjabi with English -3.43 (95% CI, -5.90, -0.97), p = .001.
Furthermore statistical significance was shown for the two-way interaction (Language
and Speaker gender) (Table 1) F(4.48,260.15) = 15.53, p < .001, η2 = .211
Table 1
Attitude means for each language as a function of gender
Language
spoken
M SD NM SD Nt p
Femal
e
Speak
ers
Male
Speak
ers
Arabic
Polish
Portuguese
Chinese
Punjabi
English
19.97
25.17
28.92
23.32
22.48
26.07
6.58
5.00
5.23
5.81
6.14
5.18
60*
60
60**
60
60
60
23.08
21.35
27.47
24.30
22.43
26.03
5.93
5.81
4.34
5.31
6.25
4.64
60
60*
60**
60
60
60
5.41
-6.47
-2.66
1.22
0.79
-0.46
.000
.000
.010
.223
.432
.642
Mean (M); Std. Deviation, Standard deviation (SD); (N) Number of participants;
*lowest M and SD
**highest M and SD
There were significant mean score differences between male Arabic and female
Arabic (t = 5.41 , p < .001); male Polish and female Polish (t = -6.47 , p < .001); plus male
Portuguese and female Portuguese (t = -2.66 , p < .05) (Table 1). No other significant
interactions were found.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 32
Further analysis to examine effect of speaker gender on attitudes revealed female
Portuguese yielding most positive attitude (M = 28.92, SD = 5.23) and female Arabic most
negative attitude (M = 19.97, SD = 6.58), (Figure a); female speakers being rated at both ends
of the positive/negative scale (Appendix B, Table 4b).
Figure a.
Total Means of attitudes towards Languages by Speaker Gender
Note: It was necessary to use colour for each Language as simply using different lines was
unclear. (Complete list of total M and SD scores for each language by participant gender; and
by speaker gender in Appendix B Table 4c and 4d for information).
An Inspection of a boxplot showed there were two outliers for female results, and
fifteen outliers for males, with no extreme outliers. Raw data revealed they were represented
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 33
by extremely negative or extremely positive attitude scores towards the language heard by the
participant. As the study was designed to record attitudes, it was deemed these should be
allowed to remain. Although assumptions of normality were mixed, ANOVA is resistant to
normality violation. Parametric tests could not support such a design, so it was deemed
appropriate to continue with the ANOVA (Schmider et al., 2010). The Levene’s test of
equality of error variances displayed (Table 2) how the assumption of homogeneity of
variances were not violated and are not statistically significant (p > .05).
Table 2
Levene’s Test of Equality of Error Variances
F Sig.
Arabic Male
Female
1.304
.006
.258
.939
Polish Male
Female
.003
.840
.956
.363
Portuguese Male
Female
1.240
2.104
.270
.152
Chinese Male
Female
.013
.045
.910
.833
Punjabi Male
Female
.007
.058
.934
.811
English Male
Female
.126
1.203
.724
.277
A test of between-subjects revealed there was no significant main effect for
participant gender F(1, 58) = 3.06, p = .085, η2 = .05 This tells us that there was no
significant difference in attitudes between male and female participants. Furthermore, there
was no significant interaction between language and participant gender F(2.94, 290) = 1.670,
p = .176, η2 = .028.
When comparing EU languages to non-EU languages and to English (Table 3) it is
shown that there is a difference in M and SD for average attitude scores towards EU
languages and English being significantly more positive than non-EU languages.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 34
Table 3
Comparison of attitudes towards EU vs Non-EU Languages
Language Groups M SD N
Average Total
EU Languages (Polish, Portuguese)
Non-EU Languages (Arabic, Chinese, Punjabi)
English
51.45
45.19
52.10
7.95
9.93
8.81
60
60
60
Mean (M); Std. Deviation, Standard deviation (SD); (N) Number of participants
*excluding English
On comparing the three language groups, the main effect of language violates the
sphericity assumption (p < .05), thus Greenhouse-Geisser correction is adopted at .705. There
was a significant main effect of language F(1.41, 81.76) = 18.82, p < .001, η2 = .245.
However the two-way interaction between Language and Participant Gender shows no
statistical significance.
Pairwise comparisons using Bonferroni correction showed there is a statistically
significant difference between EU languages and non-EU languages 6.30, (95% CI, 4.35,
8.25), p < .001); as well as between English and non-EU languages 6.69, (95% CI, 2.94,
10.43), p < .001). (Figure b) indicating more negativity towards non-EU languages.
Figure b.
Comparison of EU and non-EU Languages with English by Participant Gender
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 35
Discussion
With previous studies failing to discuss languages’ direct effects on a person’s attitude
towards the group speaking that language, other than English, within the British-born
population; the current study’s aim was to explore if attitudes towards the language differed
based on the language alone and whether gender was a factor.
Results of the three-way mixed ANOVA showed that there was a significant main
effect of language with a large effect size according to Lakens (2013); and that the
Portuguese language yielded the most positive attitude response even more than English.
Arabic netted the least positive attitude response (further supporting tables in Appendix B,
Table 4a); supporting the alternative hypothesis that spoken language does affect attitudes.
Findings contradict Clark and Schleef (2010)’s theory of participants’ loyalty to their own
spoken language over others, finding Scottish people rating Scottish English above other
English variations and Long and Preston (2002)’s research where Dutch people rate the
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 36
Dutch language more positively than other languages. This indicates UK-born people would
rate English highest, maybe limiting UK’s positivity towards other languages, yet results
show English was rated second, behind Portuguese. However Long and Preston (2002) did
argue that language did indeed affect attitudes offering an explanation as to why Portuguese
was rated most positively for both male and female speakers.
British Council research notes 75% of UK adults speak only English (Paton, 2013)
although 100 non-English languages can be heard in London, constituting 22% of its
population (ES, 2013); and 108 different languages are spoken in Birmingham at 23.8% of its
population (Carter, 2013). 42% of European teenagers (Tinsley & Board, 2014) and 54% of
all Europeans (Eurobarometer, 2012) can speak a language other than English, yet only 9% of
UK teens (Tinsley & Board, 2014), 39% of all UK citizens (Eurobarometer, 2012) are
proficient in a language other than English due to limited UK-wide exposure to other
languages (Tinsley & Board, 2014). According to the ‘CIA World Factbook’, English is only
used by 4.83% of the global population (Newsvine, 2013); 6% according to Taylor (2013),
despite being the official language in 60 different countries (Newsvine, 2013). Just 8% of
England and Wales have a first language other than English (Gopal and Matras, 2013).
Chapman (2014) reports an 80% rise of ethnic minorities in the UK since 2001 now
representing 14% of its population with further possible increases through the country’s
acceptance of refugees. Perhaps attitudes to languages other than English in the UK are
negatively biased, which Paton (2013) argues could affect the UK economically and
culturally. Results support this as Chinese, Punjabi, Polish and Arabic were all rated lower
than English.
Marshall (2013) argues UK nationals even stereotype UK people on their spoken
voice, exampled by both positively as trustworthy and intelligent for some accents such as
‘Queens English’ and negatively as having poor intelligence and unfriendly for Liverpool.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 37
BBC (2003) argue this is “British social snobbery” (BBC, 2003) and such sentiments are not
mirrored by non-British people.
When comparing EU languages with non-EU languages; and English, the results
show how EU languages were rated more positively than non-EU languages by UK citizens
(Figure b) with non-EU languages receiving a significantly lower attitude score than both EU
languages and English (Table 3). What this further indicates is that despite male and female
Portuguese speakers being rated the highest, when mixed with Polish, the results push
English to receive the most positive attitude score above both EU and non-EU languages,
once more providing an argument to support that specific languages had a bigger influence on
attitudes than others.
Results further indicated there was a significant interaction with large effect size
between language and speaker gender; specifically for male and female speakers of Arabic,
Polish and Portuguese (Figure a). However, where for Polish and Portuguese female speakers
were rated more positively, for Arabic, the female speaker was rated more negatively. One
explanation is perhaps as the male Arabic voice was deep, women find a deeper voice in men
more attractive (Simmons, Peters & Rhodes, 2011); whilst men tend to find males with
deeper voices positively more dominant (Fox, 2016). Attitudes between male and female
participants were not significant, showing relatively small effect sizes, indicating the
participant gender made little difference to the attitude scores.
It was further noted that both male and female participants rated their attitudes
towards the female speakers as either most positive or most negative (Figure a); with a trend
appearing for both male and female participants offering similar attitude scores to each other.
An equal amount of male/female speakers in their top six attitude scores (three male, three
female) for both male and female participants; and the same in their bottom six, albeit in a
different order of languages as detailed in Appendix B, Table 4b. However, as there was no
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DIFFERENT LANGUAGE TO ENGLISH. 38
statistical significant difference between male and female participants, the amount of
difference is too small to significantly affect the results.
Harris Interactive (2010) do argue that perhaps speaker gender is not as influential as
speaker tone in deciding attitudes to languages, although the results of the current study do
offer evidence that speaker gender does have an impact on attitudes. These findings are in
support of previous studies by Clark and Schleef (2010), although further qualitative tests
could examine the reasons for this decision. Harris Interactive (2010) conducted a study and
found that with the exception of car sales persuasiveness, where men preferred a male
salesman over a female; 54% of male participants stated a female had a more soothing and
persuasive tone over 38% of women who stated the same. Perhaps this offers an explanation
as to why positivity and negativity was bias towards the female ‘more persuasive’ (Harris
Interactive, 2010) speaker, as the current study consisted of 53.1% male participants.
However previous research by Carli (2001) suggests perhaps males in general emit stronger
vocal tones and greater influence in their voices than females do, thus questioning the
concept of whether males or females are more influential than the other, which could be
examined in further research.
With sentence context unknown in the current study and each sentence having the
same meaning, Arabic was rated as the most negative, which was perhaps influenced by
current media reporting of terrorist acts surrounding those who speak Arabic. Stereotyping
Arabic and Muslim nations negatively, is in agreement of reports by The Guardian (2005)
who stated 41% of 2,420 participants felt television media negatively influence western
views of Islam. This was supported by the results of this study which showed how attitudes
overall were significantly more positive towards EU languages than non-EU languages. This
could be as Beauchamp (2016) suggests, due to cultural and religious differences between the
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 39
UK and non-European nations, meaning UK accepts EU immigrants more than non-EU
immigrants.
Therefore, these results overall show that the null hypothesis (h0) is rejected and the
alternative hypothesis (h1) that ‘attitudes of UK nationals towards groups of non-English
speakers will differ positively and negatively as a function of the language under assessment’
is supported meaning spoken language does effect a persons’ attitude towards the
group/nation who speak that language. With results also supporting Long and Preston (2002),
it does leave a question as to whether spoken aesthetics makes a different to the attitude? The
findings however are sufficient to be presented to and used by the UK government to indicate
how UK citizens do display negativity towards a particular language without understanding
its context and can be used to support schemes to psychologically promote cultural diversity
and acceptance. According to Besnier (1990), people do allow their inner emotion to control
their attitude towards a speaker, which in-turn could affect how they react towards the groups
of people who speak the language, based on their experience of it. Therefore perhaps negative
media (The Guardian, 2005; Ameli et al., 2007); or prior negativity surrounding a language,
could instil a predetermined attitude towards the group who speak that language. This appears
to be the view of the Islamic Human Rights Commission within the UK (Ameli et al., 2007),
who hypothesise that Islamic representation is distorted and predominantly negative within
UK media. Furthermore, in support of this, the Australian Human Rights Commission
undertook a qualitative focus group study and found the vast majority of participants felt the
media influenced attitudes of the public negatively (Australian Human Rights Commission,
2013). However, for the UK to proceed successfully in the world in terms of security,
international relations, trade and diplomatic purposes, Taylor (2013) argues that the country
must be multilingual. Therefore, perhaps with prior and the current study findings,
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 40
governmental educational schemes can improve the attitude of the UK public towards other
languages and in-turn groups of people who speak a language other than English, in the UK.
Limitations
A few reports were received from participants who had completed the survey using an
ipad and stated that the initial page containing the study information, was in script on ipad,
despite it being standard ‘comic sans’ on the computer. Where this could be a limitation and
potentially put off participants in going further with the study (Soleimani & Mohammadi,
2012). Those who reported this did say that it did not prevent them from continuing with the
study, despite the information being a little more difficult to read. Perhaps further studies
would need to be with a different survey provider to prevent repeated issues.
Another limitation was that with no emotion, very few people speak with no
emotions, in a monotone way, so perhaps the spoken language was not a true representation
of how the language would typically be heard meaning linguistic aesthetics should be
factored into the study. Further studies should perhaps adapt this technique so the voice could
be spoken in a natural ambient environment, or use a ‘matched guise technique’ where one
speaker is used for all languages under assessment.
One issue was time restraints. Once proposal and ethics approval were received, it left
just two months for adequate data collection and having exhausted appropriate social media
pages, university communities and websites, gathering valid participant responses proved to
be extremely difficult. Thus sample size was a subsequent limitation, and further studies
should allow more time and a larger sample size to create a more valid sample for the
population.
Due to the small sample size and sporadic age demographic, to avoid potential bias it
was not possible to group responses by age to test if it were a contributing factor. From the 60
valid responses, the participant sizes were grouped age 18-24 (9), age 25-40 (18), age 41-59
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 41
(26), age 60+ (7). However, a larger sample in the future may permit grouping by age in order
to produce valid results.
There is a risk of ‘Response Bias’ (Leavitt, 1977) from participants who feel their
answers should be more favourable towards certain groups due to an inner feeling of not
wanting to appear too negative, however as the responses are anonymous, the risk is minimal
with the confidence interval in the analysis allowing for this. Furthermore, the results do not
take into account the participants personality type (Dias, 2012); where different personalities
may interpret a language or vocal tone dissimilarly.
Positive change
Therefore, with a nation such as the UK that is diverse in cultural and lingual
differences, these differences are what drives the UK and being aware and accepting of them
is what makes the country flow successfully with inter-cultural interactions providing a
greater chance for prosperity (Wood, Landry & Bloomfield, 2006). Positive change towards
other languages and cultures in the UK has been shown (Crouch & Stonehouse, 2016)
although there is room for greater improvement. There is a significant argument for UK-born
citizens to be aware of different languages and comprehend that as the language is perhaps
not understandable, does not equate to it being negative. With negative attitudes towards
particular languages as indicated in this study and portrayed through media (Buckley, 2012);
and as noted by Marshall (2013) already present between accents within the English
language, only strengthens the argument for schemes to improve the UK publics’ ability to
accept linguistic diversity.
Conclusion and Recommendations
Conclusion
In conclusion, with the question as to whether attitudes towards a group of people were based
on the language heard, results from the online quantitative study indicated that UK-born
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 42
citizens’ attitudes did alter depending on the language heard, in line with the alternative
hypothesis, further affected by the gender of the speaker but not the gender of participant. As
immigration is an ongoing world topic of debate, non-EU languages appear to be less positive
than EU languages, thus educating the UK public through multicultural publications and
positive messages to come together and not form separate communities, may improve
tolerance and acceptance (Crouch & Stonehouse, 2016); especially with increasing instances
of language variety in the UK (Jivraj, 2012; Lessard-Phillips, 2015). Opinions and attitudes
towards other languages for UK born citizens inevitably differ although a country rich in a
plethora of international difference highlights the importance for the UK government to help
educate its population to accept language diversity and not to be weary of it. Despite
negativity portrayed in the media (Ameli et al., 2007); dispersing of predetermined prejudices
and fully understanding the context before passing judgement is important. To aid tolerance
of lingual and cultural diversity, schemes to encourage acceptance are vital for a forward
thinking nation.
Recommendations for future studies.
During the study’s active period, an email from a participant indicated they would
have preferred to know the context of the sentences before registering a feeling towards the
language. This study forced people to make a judged feeling based on the language rather
than context, which highlights a potential debate on the importance of language context
before making an emotionally charged decision towards a language. Perhaps a future study
could involve an additional follow-up English translation, then pose the question again to see
if participants registers a different feeling.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 43
Future studies could also involve a follow-up survey to include a visualisation to
accompany the voice, a picture of a typical person using this voice in a positive way and in a
negative way to explore if ‘context or visual aid’ affects the attitude towards the language or
group who speak it.
As age could not be measured as a factor for this study due to sample size restrictions
meaning results would be too little to hold validity; further study with a larger sample may
render this a valid measurement in the future.
Additionally, where a quantitative study was detailed for this dissertation by the
University, perhaps a qualitative study may have yielded clearer understanding of attitudes
towards other languages other than English, heard within the UK through discussions with
participants, perhaps as argued to give better reasoning for their opinion by Pathak, Jena and
Kalra (2013). Therefore maybe qualitative methods can be used in conjunction with
quantitative surveys, to first identify the groups through semantic differential scales, before
examining the reasons behind the responses, through qualitative questioning, noted as an
effective method by Eirich and Corbett (2009).
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Perceived Realism. International Journal of Communication, 9, 1-20.
Appendices
Appendix A
Questionnaire design
An example of the scale used in this study is shown below:
Each of the voices were marked through five, 5 point scales as shown below:
SDLS 1: Bipolar Attitude Scale
Voice 1 I found this language to be:
1 2 3 4 5
cold [_____[_____[_____]_____]_____] warm
angry [_____[_____[_____]_____]_____] calm
displeasing [_____[_____[_____]_____]_____] pleasing
complex [_____[_____[_____]_____]_____] simple
frustrating [_____[_____[_____]_____]_____] acceptable
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 53
SDLS 2: Feeling-led Attitude Scale
Voice 1 Q1: I would be comfortable around this person
Strongly Somewhat Neutral Somewhat Strongly
disagree disagree agree agree
1 2 3 4 5
Q2: I would be anxious/worried around this person
Strongly Somewhat Neutral Somewhat Strongly
agree agree disagree disagree
1 2 3 4 5
Appendix B
Table 4a
Positivity / negativity towards language
1 – Most Positive Portuguese
English
Chinese
Polish
Punjabi
6 – Most Negative Arabic
1 being most positive and 6 being most negative,
Table 4b
Order of attitudes for female and male participants by language and speaker gender
Female Participants Male Participants
1 – Most Positive Female Portuguese Female Portuguese
Male Portuguese Male Portuguese
Female English Male English
Female Polish Female English
Male English Male Chinese
Male Arabic Female Polish
Male Punjabi Female Chinese
Male Chinese Male Arabic
Female Chinese Female Punjabi
Female Punjabi Male Punjabi
Male Polish Male Polish
12 – Most Negative Female Arabic Female Arabic
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 54
Table 4c
Female vs male participant comparison: Attitude means for each language and total scores
Language
spoken
M SD NM SD NM SD N
Female Participants Male Participants TOTAL m+f participant
Arabic
Polish
Portuguese
Chinese
Punjabi
English
46.35
49.19
58.81
47.85
47.85
52.42
9.48
8.99
7.99
10.10
10.31
8.90
26
26
26
26
26
26
40.53
44.47
54.53
47.44
42.68
51.85
12.53
10.18
8.98
10.25
11.71
8.88
34
34
34
34
34
34
43.05
46.52
56.38
47.62
44.92
52.10
11.59
9.89
8.75
10.12
11.33
8.81
60*
60
60**
60
60
60
Mean (M); Std. Deviation, Standard deviation (SD); (N) Number of participants; (m) male;
(f) female.
*lowest M and SD
**highest M and SD
Table 4d
Female vs male participant comparison and total scores: Attitude means for each language
by speaker gender
Language by
spkr gender
M SD NM SD NM SD N
Female Participants Male Participants TOTAL m+f participants
m Arabic
f Arabic
m Polish
f Polish
m Portuguese
f Portuguese
m Chinese
f Chinese
m Punjabi
f Punjabi
m English
f English
24.46
21.88
22.96
26.23
28.85
29.96
24.19
23.65
24.23
23.62
26.00
26.42
5.03
5.92
5.13
4.32
3.64
4.94
5.14
5.64
5.55
5.77
4.86
4.86
26
26
26
26
26
26
26
26
26
26
26
26
22.03
18.50
20.12
24.35
26.41
28.12
24.38
23.06
21.06
21.62
26.06
25.79
6.40
6.77
6.06
5.39
4.59
5.38
5.52
6.01
6.47
6.36
4.54
5.47
34
34
34
34
34
34
34
34
34
34
34
34
23.08
19.97
21.35
25.17
27.47
28.92
24.30
23.32
22.43
22.48
26.03
26.07
5.93
6.58
5.81
5.00
4.34
5.23
5.31
5.81
6.25
6.14
4.64
5.18
60
60
60
60
60
60
60
60
60
60
60
60
*
**
Mean (M); Std. Deviation, Standard deviation (SD); (N) Number of participants; (m) male;
(f) female; (spkr) speaker
*lowest M and SD
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 55
**highest M and SD
Appendix C
Study Proposal
INTERNATIONAL ONLINE RESEARCH ETHICS COMMITTEE
APPLICATION FOR APPROVAL OF A PROJECT INVOLVING
HUMAN PARTICIPANTS, HUMAN DATA, OR HUMAN MATERIAL
Student applications to the online programmes’ International Online Research Ethics Committee, with
the specified attachments, should be posted to the Dissertation Advisor’s classroom. If the
Dissertation Advisor refers the application on the ethics committee, the DA must email the full
application as a single, zipped file to liverpoolethics@ohecampus.com.
RESEARCH MUST NOT BEGIN UNTIL ETHICAL APPROVAL HAS BEEN OBTAINED
This form must be completed by following the guidance notes, accessible at
www.liv.ac.uk/researchethics.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 56
Please complete every section, using N/A if appropriate.
Incomplete forms will be returned to the applicant.
Declaration of the:
Principal Investigator       OR Supervisor and Student Investigator X
(please enter an X as appropriate)
The information in this form is accurate to the best of my knowledge and belief, and I take full
responsibility for it.
I have read and understand the University’s Policy on Research Ethics.
I undertake to abide by the ethical principles underlying the Declaration of Helsinki and the
University’s good practice guidelines on the proper conduct of research, together with the
codes of practice laid down by any relevant professional or learned society.
If the research is approved, I undertake to adhere to the study plan, the terms of the full
application of which the REC has given a favourable opinion, and any conditions set out by
the REC in giving its favourable opinion.
I undertake to seek an ethical opinion from the REC before implementing substantial
amendments to the study plan or to the terms of the full application of which the REC has
given a favourable opinion.
I understand that I am responsible for monitoring the research at all times.
Office Use Only (for final hard copies)
Reference Number: RETH
     
Date final copy received:
Approval decision:
Approved – no conditions      
Committee      
Chairs Action      
Expedited      
Approved with conditions      
Committee      
Chairs Action      
Expedited      
     
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 57
If there are any serious adverse events, I understand that I am responsible for immediately
stopping the research and alerting the Research Ethics Committee within 24 hours of the
occurrence, via ethics@liv.ac.uk.
I am aware of my responsibility to be up to date and comply with the requirements of the law
and relevant guidelines relating to security and confidentiality of personal data.
I understand that research records/data may be subject to inspection for audit purposes if
required in future.
I understand that personal data about me as a researcher in this application will be held by
the University and that this will be managed according to the principles established in the
Data Protection Act.
I understand that the information contained in this application, any supporting documentation
and all correspondence with the Research Ethics Committee relating to the application, will be
subject to the provisions of the Freedom of Information Acts. The information may be
disclosed in response to requests made under the Acts except where statutory exemptions
apply.
I understand that all conditions apply to any co-applicants and researchers involved in the
study, and that it is my responsibility to ensure that they abide by them.
For Supervisors: I understand my responsibilities as supervisor, and will ensure, to the best
of my abilities, that the student investigator abides by the University’s Policy on Research
Ethics at all times.
For the Student Investigator: I understand my responsibilities to work within a set of safety,
ethical and other guidelines as agreed in advance with my supervisor and understand that I
must comply with the University’s regulations and any other applicable code of ethics at all
times.
Signature of Principal Investigator       or Supervisor X : ....Stamatis Elntib.....
Date: (27/07/2016)
Print Name: Stamatis Elntib
Signature of Student Investigator: Mark A. Whittington-Buckley
Date: 06/05/2016
Print Name: Mark Anthony Whittington-Buckley
SECTION A - IDENTIFYING INFORMATION
A1) Title of the research (PLEASE INCLUDE A SHORT LAY TITLE IN BRACKETS).
Spoken language: UK attitudes towards people who speak a different language to English.
Introduction and background
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 58
A2) Principal Investigator       OR Supervisor X (please check as appropriate)
Title: Dr Staff number:      
Forename/Initials: Stamatis Surname: Elntib
Post: HL Department:      
Telephone:       E-mail:      
A3) Co-applicants (including student investigators)
Title and
Name
Post / Current
programme (if
student
investigator)
Department/
School/Institution
if not UoL
Phone Email
Mr Mark
Anthony
Whittington-
Buckley
Masters (Msc)
Psychology
University of
Liverpool
07944
611212
stormy22@live.co.uk
                             
                             
                             
                             
                             
SECTION B - PROJECT DETAILS
B1) Proposed study dates and duration (RESEARCH MUST NOT BEGIN UNTIL ETHICAL
APPROVAL HAS BEEN OBTAINED)
Please complete as appropriate:
EITHER
a) Starting as soon as ethical approval has been obtained X(please check if
applicable)
Approximate end date: 28th December 2016
OR
b) Approximate dates:
Start date: 20th June 2016 End date: 20th December
2016
B2) Give a full lay summary of the purpose, design and methodology of the planned
research.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 59
DISSERTATION PROPOSAL PRO FORMA
FORENSIC PSYCHOLOGY & CRIMINAL
INVESTIGATION/APPLIED PSYCHOLOGY PROGRAMMES
Student Name: Mark A. Whittington-Buckley
Dissertation Advisor: Stamatis Eldib
Title
Spoken language: UK attitudes towards people who speak a different language
to English.
Introduction and background
There has been an 80% rise in the ethnic minority population in the UK since
2001 (Chapman, 2014); now representing 14% of the population of the UK with
the possibility of this figure increasing following the admission of refugees.
However, only 9% of UK teenagers are proficient in a language other than
English, compared to 42% of their European counterparts (Tinsley & Board,
2013). Gopal and Matras (2013) argued that 8% of the population of England
and Wales have a first language other than English; with over 100 languages in
London; 22% of London population (ES, 2013); and a similar situation in
Birmingham with 23.8% being born outside the UK and 108 different languages
spoken around the city (Carter, 2013).
Therefore, with the level of ethnic minorities increasing within the UK (Jivraj,
2012), it is likely UK nationals will experience another language spoken other
than English. The purpose of this study is to explore how UK nationals feel
towards and make judgements on non-English speaking groups of people based
only on their spoken language. Meadows (2009) argued, people visualise an
expectation when they hear a language, reflecting a personal feeling towards that
person. This in-turn may result in forming an opinion, influencing an attitude
towards the group speaking that language. Therefore, understanding British
attitudes towards other languages and whether it affects their judgement of the
group speaking that language, is important in order to introduce measures to
encourage acceptance within the UK. Without such acceptance the likelihood of
current increasing negative attitudes such as racist thoughts and comments
towards non-English speaking groups, could be exacerbated (Taylor & Muir,
2014).
Literature Summary
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 60
With spoken language being the focus, in reviewing literature it was noted little
previous evidence of attitudes towards groups of people based on their spoken
language, existed until recently. As McKenzie (2015) acknowledged; together
with Clopper and Pisoni (2007), who focussed their research on whether people
perceive a persons’ regional origin by grouping English speakers and assigning
them to a particular area of the US. Ethnically, by age and gender based on their
spoken voice, they measured how participants found similarities between
regional dialects within the USA. Findings indicated that vowel sounds
distinguished where the speakers originated within the USA, leading them to
investigate if participants could correctly guess where speakers originate from
within the USA. Results showed that vowel sounds were the biggest influence
on interpreting correct speakers’ regional dialects. In one task, participants who
had previously been around a particular regional dialect showed greater
detection of that dialect, showing ‘prior experience’ was an influential factor.
Furthermore, as Dicker (2003) argues, many Americans tend to prejudge a
person’s level of intelligence based on their accent, for example deeming Latin
Americans as having low intelligence; in-turn affecting the Spanish language
meaning the residents of both Mexico and Spain are viewed by many Americans
as having low intelligence (Dicker, 2003). Therefore the results of this study
could be influenced by a participants personal bias of a particular accent or
language they hear. Kite and Whitley Jr (2012) concentrated on the positivity or
negativity of stereotypical English phrases and their use of other nations in their
daily phrases, i.e. ‘excuse my French’, ‘Indian giver’, ‘get off scot free’. Results
from their sample of 34 social psychology students did show an increased self-
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 61
awareness of how they stereotype certain people based on these phrases;
rendering the majority of phrases as having negative connotations. Therefore
with the exception of the phrase ‘Dutch Treat’ seen as being used positively, the
rest of the phrases in the study were seen as using negative words and being
viewed by participants as only being used to describe a person’s behaviour
negatively. This in-turn allowed people in general to think negatively towards
groups of people from a certain nation through the use of said negative phrases
such as those mentioned above (Kite & Whitley Jr, 2012). However, with such a
small sample and specifically a group of students, the results cannot be
generalised for a large varied population. Kulkarni and Sommer (2014)
presented a theoretical perspective rather than an empirical study, discussing
how linguistic diversity within Indian workplaces caused exclusion amongst
peers, resulting in people feeling less accepted and less willing to help
colleagues. However without an empirical study, no actual findings were
presented. Dotan-Eliaz, Sommer and Rubin (2009) reported that those who were
excluded due to language barriers were more likely to present with greater anger
and less attraction towards colleagues; and less likely to reintegrate with the
main group, with depleted levels of effort. Tenzer and Pudelko (2015) reported
results through qualitative interviews, discussing how multinational teams with
people from a variety of cultural backgrounds face language barriers, such as
misunderstanding context, unable to translate discussions into their own
language and read different cultural expressions, to aid understanding of the
theme of the conversation. These can disrupt the flow of work and working
relationships. This in-turn can cause negative emotions such as aggravation,
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 62
anxiety, embarrassment and stress; affecting problem solving skills, elongating
methods to overcome work issues and attitudes towards colleagues of a different
nationality. As a result, with work relationships tense, language barriers were
seen as affecting performance and productivity in multinational organisations
adversely. Moreover, their study also showed that leaders of multinational teams
can avoid negative attitudes by embracing linguistic diversity rather than seeing
it as a barrier. However thematic coding analysis meant data was difficult to
quantify and compare.
Similarly, Zhang (2010) reported exclusion and peer rejection by society within
the USA, through examining stereotyping by the general public, ability to
communicate effectively and ability to create friendships in general. Zhang
(2010) reported that Asian Americans are under-represented in media, such as
TV programmes, due to negative stereotypes made about them by US society as
‘nerdy, passive and quiet’ and favouring using their own language over English.
Using 169 students of varying ethnic background, Zhang (2010) reported that
media-fed perceptions predicted Asian Americans would have poor
communication and language skills, be more likely to be excluded by peers and
be less likely to form friendships, with Asian’s often being greeted by “Do you
speak English?” And “Where are you really from?” (Cheryan & Monin, 2005).
Results were found to be in line with media expectations, indicating their
perception was correct. Moreover, exclusion stemmed from US nationals
attitudes stereotyping Asians as ‘evil’ and ‘untrustworthy’ leading to hate crime,
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 63
discrimination and rejection by US nationals (Kawai, 2005). Limitations
however were that the sample were predominantly white, middle class student
Americans. Additionally, the results did not show why participants agreed with
media perceptions; and the scenarios used were hypothetical and unrealistic.
However, McKenzie (2015) focused on how UK nationals identify a person’s
origin based on their language and accent, using six speakers, three from East-
Asian nations, two from the UK and one Indian, limiting its research mostly to
one specific continent. Their results indicated a significant number of
participants were able to nominate an origin of the language although their
findings were limited as the reaction to the individual speaking the language,
was not investigated.
Clark and Schleef (2010) examined the attitudes of native English speakers
towards 34 UK accents to include Glaswegian, Edinburgh, Welsh, Birmingham
and Indian English, on a pleasantness scale. Non-standard English accents -
Irish, Scottish, Afro-Caribbean English and the Northeast English accents were
rated the most pleasant to hear. Moreover, Birmingham accent was seen as the
least attractive and although the RP (Queen’s English) was marked as the most
prestigious, it was not seen as attractive. Further, female voices were seen as
more pleasant than male and regional/geographical loyalty affected a significant
number of choices in that participants from Scotland rated Scottish English more
prestigious than other regional variants of English, from England. However, its
main limitation, like Kite and Whitley Jr (2012), is the low sample size used
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 64
(N=37) and that it cannot be generalised. Therefore the purpose of this study is
to examine how different spoken languages common within the UK, impact on
people’s attitudes towards the groups who speak them, addressing age and
gender of the speakers and participants as variables, examining the attitudes to
different language, rather than only accents. With an increasing presence of non-
English languages in the UK (Chapman, 2014), understanding linguistic
diversity can help to eradicate prejudice towards groups of people based on the
language they speak by showing that speech may influence an attitude towards a
particular group of people, without knowing what is actually being said.
Therefore, to test whether spoken language does affect UK nationals attitudes
towards a particular group of speakers, the hypotheses for this research are:
H0: The attitudes of UK nationals towards groups of non-English speakers will
not differ significantly as a function of the language under assessment.
H1: The attitudes of UK nationals towards groups of non-English speakers will
differ significantly as a function of the language under assessment.
Research Question
Do foreign spoken languages influence UK nationals’ attitudes towards non-
English speaking groups?
Aim(s) and Objectives
Aim:
To explore the attitudes of UK nationals toward non-English speaking groups
with the UK.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 65
Objectives:
To measure the attitudes of UK nationals towards different spoken languages
To assess gender and age effects of speaker and response participant on UK
nationals’ attitudes towards non-English and English speakers.
To investigate attitude differences as a function of the five non-English
languages, and English language spoken.
Methods
Design:
As participants will be answering a questionnaire immediately upon hearing the
different languages, registering their attitude towards each language, without
further follow-up; the research design would be ‘cross-sectional’ with variables
language(s) (IV); and attitudes (DV) to measure the frequency of a specific
occurrence (attitude choice) at one time. Matched guise technique (MGT) could
be ruled out as finding a single speaker to speak a wide variety of languages with
authentic fluency would be too difficult. Therefore, verbal guise technique
(VGT) is selected, where different speakers would be used, both male and
female for each language.
Participants:
Response participants will be sought through social media advertising
(Facebook, Twitter, Youtube video advert). Participants will be UK born with
English as their main or only language.
To gain a reliable average of each age and gender, using a non-probability quota
sampling strategy, data will be gathered and then results will be distributed
between males and females. Then without concern for Socio-economic status,
gathered data will include age in order for age means scores to be used and
create age groups depending on the distribution, to determine if age is a factor in
attitude towards language.
Sample-size calculation:
To calculate the sample size, the following calculation was undertaken, using
Statcal-EpiINFO Version 7.1; using the formula
(1.96 2*p(1-p))/e2
Where p=0.5 (50% - as there is no existing data) and e=0.05 (5%), the minimum
sample size required would be 384. Therefore 400 participants will be chosen
from the British born population within the east coast of England which has
6.5% non-UK born population (Qpzm, 2012); ensuring there is an equal amount
of male and female participants, covering all adult age ranges.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 66
Inclusion Criteria:
All UK-born, British males and females between the ages of 18 and 80, with
English as their only, or main language. (Main is indicated as those English-born
who can also speak a second language i.e. French, German or another can be
included within the study).
Exclusion Criteria:
Any person who is not born in the UK and considered to be an ethnic minority
with a main language other than English.
Anyone UK-born who has a main language other than English.
Procedure:
Stimuli participants’ recruitment
Stimuli participants used for the production of the stimuli will be recruited from
a pool of associates of the student researcher, approached through ‘Facebook-
friends’. Preliminary discussions have aided the researcher to identify the
majority of the 12 different “speakers” required for the research. Upon receipt of
ethical approval, a voluntary invite shall be sent to all interested stimuli
participants, explaining the requirements and the purpose of the study in greater
detail, seeking their official permission to participate. Upon proposal acceptance,
the male and female speakers will be recruited for their anonymous assistance.
Upon agreement to continue and consent to use their voice for the study stimuli,
electronically signed through a tick-box; the speakers will be asked to read four
short sentences in their own language:- Chinese, Punjabi, Polish, Portuguese,
Arabic and English; both male and female, using a recording device with no
background noise. The stimuli participants will then email the voice sample to
the student researcher. This method is preferred and deemed to be most
successful as the stimuli participants are already aware of the Masters course
undertaken and have previously expressed interest in offering voluntary
assistance when required. Furthermore, using this method, the student researcher
can request the same specific non-emotive sentences for all languages.
Each stimuli participant used from the pool will be bilingual and fluent in both
English and their own native language, thus are able to translate the sentence
required properly into their natural native spoken language. Each speaker shall
record the following non-emotive sentence:
First you break an egg into a bowl. Then mix with sugar and add some
milk. After this, cover your baking tray with paper. Put the ingredients on
the tray and bake in the oven.”
The stimuli consisting of the six different languages in both male and female
voices, shall be uploaded to the wix hosting site and used within the survey
questionnaire in ‘Qualtrics’ (Qualtrics, 2016). Each can be played by the
participants prior to answering the 7-item questionnaire for each voice.
Response participants’ recruitment
Research response participants will be recruited through online advertising
within social media applications ‘Facebook’ and ‘Twitter’ being the most
popular amongst the general population throughout the UK, and most likely to
attract a UK wide range of participants. A further recruitment method shall use
online discussion groups of the study and website within Liverpool University
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 67
Laureate community. Information will include the study’s purpose, inclusion and
exclusion criteria, proposed outcome and contact details for further information.
Participant recruitment will be on a voluntary basis and will continue until the
participant quota is fulfilled. Data will be collected through ‘Qualtrics’
(Qualtrics, 2016) with a link to a website hosted by wix.com which will hold all
twelve voices, being male and female speaking ‘Chinese, Polish, Punjabi,
Arabic, Portuguese and English’, chosen for being the languages most likely to
be heard in the UK according to the 2011 census (English – 1st most likely,
Polish – 2nd , Punjabi – 3rd , Arabic – 7th , Chinese – 9th , Portuguese – 10th)
(Evans, 2013). Participants will complete each short 7-item questionnaire after
listening to each voice.
Participants will be informed that all answers are confidential and only their
gender and age shall be recorded. They will be informed via a statement on the
page leading to the questionnaire that by clicking the ‘tick-box’, they are
confirming they are UK-born with a main language of English; agreeing to the
instructions and that they understand the purpose of the study, giving consent
that their responses in the research questionnaire be used as part of the study. For
those who agree to continue, survey questionnaires and voice links, together
with information about the study will be provided for potential participants.
Participants will be asked to record their response on the form provided through
‘Qualtrics’ with numbers 1 – 12, corresponding with numbers 1-12 voices heard.
Participants will be informed that the survey is likely to take between 15 and 20
minutes to complete, with an approximate time of 1 minute spent for each voice.
Data will then be collected anonymously, as no personal details are required by
participants except gender, age and acknowledgement of being UK-born with
English as a main or only language; through ‘Qualtrics’; and downloaded
anonymously.
Data Collection/Materials:
Each questionnaire will detail each participants’ demographic data to include age
and gender.
Participants sheet will consist of two questionnaires, used to determine the
‘attitude scores’ (DV) incorporating 2 parts; 2 Semantic Differential scales
‘SDLS1: Bipolar Attitude Scale’ and ‘SDLS 2: Feeling-led Attitude Scale’.
Questionnaire 1 (SDLS1): Data will be collected using a Qualtrics sheet
recording responses on a Semantic Differential Likert Scale (SDS) using 5 sets
of bipolar (opposite) adjectives, argued to be a valid measurement of attitudes by
Heise (1970) and used in a study by Nickols and Shaw (1964) to measure
attitudes towards college professors and towards the Church, supporting its
validity. More recently, Ajani and Stork (2013) used SDS to measure attitudes
towards emerging technologies using a 10-item, 2 factor bipolar scales through a
confirmatory factor analysis and found the method to be simple and reliable in
quantifying attitudes.
In this study, SLDS 1 “Bipolar Attitude Scale” will record attitude responses to
each voice heard, using a bipolar adjective scale (Osgood et al., 1957). In line
with the methods used by Ajani and Stork (2013), scores for each item will be
added into a total score, then divided by the number of items (5) to reach each
participant’s score, following the method of Ajani and Stork (2013) once more,
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 68
scores will be interpreted thusly 0-0.99 = very negative attitude; 1-1.99 =
negative attitude; 2-2.99 = Neutral/unsure; 3-3.99 = positive attitude; 4-5 = very
positive attitude, indicating participants attitude scores towards the language
they hear.
Ajani and Stork (2013) showed a reliability rating of 0.85 using this scale which
indicates a ‘good’ rate of reliability for using SDS. According to Cronbach’s
Alpha (Cronbach, 1951; Santos, 1999; Nunnally, 1978); anything over 0.70,
being ‘acceptable’ is a good rate of reliability. With Ajani and Stork’s high level
of reliability noted, it indicates a very good scale to incorporate into the current
study. However, the scales for this study have been chosen, not by using
another’s scale, but by selecting relevant attitude measurements for this
particular study, although using the same format as used by Ajani and Stork
(2013).
An example of the scale to be used in this study is shown below:
Each of the voices will be marked through five, 5 point scales as shown below:
SDLS 1: Bipolar Attitude Scale
Voice 1 I found this language to be:
1 2 3 4 5
cold [_____[_____[_____]_____]_____] warm
angry [_____[_____[_____]_____]_____] calm
displeasing [_____[_____[_____]_____]_____] pleasing
complex [_____[_____[_____]_____]_____] simple
frustrating [_____[_____[_____]_____]_____] acceptable
SDLS 2 “Feeling-led Attitude Scale” will measure participants’ feelings towards
the person who has spoken. Scored on a 5 point Likert scale (Likert, 1932) and
again in line with the methods used by Ajani and Stork (2013), scores for each
item will be added into a total score, then divided by the number of items (5) to
reach each participant’s score. Following the method of Ajani and Stork (2013)
once more, scores will be interpreted thusly 0-0.99 = very negative attitude; 1-
1.99 = negative attitude; 2-2.99 = Neutral/unsure; 3-3.99 = positive attitude; 4-5
= very positive attitude, indicating participants attitude scores towards the
language they hear.
Questionnaire 2 will consist of two questions, on a 5 point Likert scale after the
Semantic Differential scale (SDLS1) for each voice. There are two opposing
questions (1 positive question and 1 negative question). Therefore, for both, 5
equals a positive response and 1 equals a negative response with the responses
being reversed to keep the scoring consistent, rather than having to reverse the
scoring itself manually.
Participants will register their attitude towards the group of people who speak
this language. For example:
SDLS 2: Feeling-led Attitude Scale
Voice 1 Q1: I would be comfortable around this person
Strongly Somewhat Neutral Somewhat Strongly
disagree disagree agree agree
1 2 3 4 5
Q2: I would be anxious/worried around this person
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DIFFERENT LANGUAGE TO ENGLISH. 69
Strongly Somewhat Neutral Somewhat Strongly
agree agree disagree disagree
1 2 3 4 5
With initial uncertainty as to whether a 5-point or 7-point Likert scale would be
used for this study; Preston and Colman (2000) indicated in a study that a 7-
point scale does yield a slightly higher reliability than a 5-point scale. However,
both 5 and 7 point Likert scales are calculated as more reliable over other Likert
scales with higher or lower points, by its participants (Preston & Colman, 2000);
meaning a 5 or 7 point scale is acceptable for this study.
Furthermore, Finstad (2010) argues that a 7-point Likert can give a more
accurate representation of a participants true feelings. However, within the
current study, the two simple questions indicate a 5-point scale would be
adequate as the questions encourage either a positive or negative response rather
than a sliding scale of positivity or negativity. Therefore anything more than a 5
point scale would be unnecessary to score and offer too much of a variety of
positivity, or negativity. In short, scores will show the amount of participants
choosing a number between 1 and 5 which will indicate how they feel towards
the language they hear.
As both scales register positive or negative attitudes towards the voice heard, a
comparison can be made to show consistency of responses for participants.
Overall each voice heard would have 7 quick response questions in total.
Following this, the sum of item scores for each part (scale) shall be added
together which will form the TOTAL score for each part (scale); to be used in the
analysis, eliminating the necessity to conduct analysis of each item separately.
This method was successfully used and proved a reliable method by Jha,
Bajracharya and Shankar (2013) in their research to understand attitudes to
medicine before and after educational intervention.
Statistical Analysis:
Using SPSS, a three-way mixed ANOVA will be used with repeated measures on
speaker gender (i.e. male/female); and language spoken (i.e. Chinese, Polish,
Punjabi, Portuguese, Arabic and English); plus between-subjects factor the
response-participant gender. It is also aimed to control for response-participant
age by using ‘age’ as a covariate or alternatively, depending on age distribution
and final sample size, introduce age as an additional ‘between-subjects’ IV.
In determining if different languages heard (IV) affects attitudes (DV), towards
an ethnic group; and whether gender of the person speaking that language makes
a difference to the attitude; the within-subject independent variables (IV) would
be ‘language’; including 6 levels:- Chinese, Polish, Portuguese, Punjabi, Arabic
and English. ‘Gender of speaker’ would serve as the within-subject IV’s; and
gender of response participants will be the between-subject IV both having two
levels, 2 male/female.
With the results set to show if the null hypothesis (h0) or alternative hypothesis
(h1) are true, a marginal P value is appropriate at 0.05 (P=0.05).
Using IBM SPSS Statistics Version 21, raw scores will be converted to Z-scores,
to obtain standard deviation for the data. As the population size will be over 30,
a Z or T score can be used, especially as the population SD (Standard Deviation)
can be calculated, using the formula
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 70
(Raw scores will added and divided by the amount of items to calculate the
mean score for each scale. Then the distance from each raw score to the mean
will be calculated by adding each score squared to gain the average which will
equal the variance (average squared distance to the mean). The square root of
this figure will give the Standard Deviation ( ) (Average distance to the
mean).
To eliminate negative scores and without having to working with negative
figures, making the calculations easier to interpret, the Z-scores accumulated
from the Semantic Differential Scales, which have a mean of 0 and standard
deviation of 1; will then be converted to T-scores which have a mean of 50 and a
standard deviation of 10. (T=50+10xZ).
Ethics:
Ethics approval shall be applied for and gained from the Ethics Committee of the
University of Liverpool.
Although participants will be found on a voluntary basis through the survey
supplier, participants will reserve the right to withdraw from the study, or having
read the research brief, refuse the right to participate at any time.
Participants must give consent by reading a statement and clicking a tick-box to
show they understand the purpose of the study, agreeing to participate and
provide opinion before continuing.
Through coding and numbering of participants responses (m1 = male respondent
1, f1 = female respondent 1; ms1 = male speaker 1, fs1 = female speaker 1, and
so on); participants anonymity and confidentiality at all times shall be assured
with raw collected data only to be viewed by the researcher and dissertation
advisor and study data stored on a password protected computer, and kept for 5
years after the study has ended. Data shall not be shared with any organisation.
Introduction of this study may induce attitudes towards a language, and in-turn
towards a group of people (race) that did not previously exist prior to the study,
as such allowing participants to think about their views towards a race which
could result in negative attitudes towards them.
Non-UK born participants who now hold British citizenship/nationality may feel
excluded from being ‘British’ although this will be addressed in the study
statement.
It is not anticipated that expedited or full ethics approval shall be required as no-
one involved in the study are likely to come to any harm, or be at risk of any
harm.
Research Outcomes
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 71
To gain an understanding of attitudes of UK-born individuals towards
people using other spoken languages within the UK.
The findings of this research shall be presented to the community services
department of the local council where the raw research was undertaken (Norfolk
County Council) (NCC, 2015-2016) to provide awareness of attitudes to
languages and potentially aid the council to create measures to help community
cohesion and acceptance. The findings will also be further presented to the
Department for Communities and Local Government (GOV. n.d.) as advice on
the community attitudes to other languages for the government to implement
strategies to improve UK citizens acceptance of others and community diversity
awareness.
Costs
All costs will be met by the student researcher.
Timetable
Milestone Description Due Date Remarks
1 Stage 1: Area of interest identified Already met
2 Stage 2: Specific topic selected Already met
3Stage 3: Topic refined to develop
Dissertation Proposal
Already met
4Stage 4: Proposal written and
submitted
Already met
5Stage 5: Collection of data and
information
June-July
2016
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 72
6
Stage 6: Analysis and
interpretation of collected
data/information
August
2016
7
Stage 7: Writing up September
– October
2016
8
Stage 8: Final draft prepared—
submission of
dissertation
October –
November
2016
9Final deadline—nine months from
classroom date
December
2016
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B3) List any research assistants, sub-contractors or other staff not named above who will
be involved in the research and detail their involvement.
None
B4) List below all research sites, and their Lead Investigators, to be included in this study.
Research Site Individual Responsible Position and contact details
n/a – internet-based
study
           
                 
                 
B5) Are the results of the study to be disseminated in the public domain?
YES X NO      
If not, why not?
B6) Give details of the funding of the research, including funding organisation(s), amount
applied for or secured, duration, and UOL reference
Funding Body Amount Duration UoL Reference
None None None None
                       
                       
B7) Give details of any interests, commercial or otherwise, you or your co-applicants have
in the funding body.
     
Not Applicable
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 76
SECTION C - EXPEDITED REVIEW
C1)
Yes or
No?
a) Does the study involve participants who are particularly vulnerable or unable
to give informed consent? (e.g. children, people with learning or communication
disabilities, people in custody, people engaged in illegal activities such as drug-taking,
your own students in an educational capacity) (Note: this does not include secondary
data authorised for release by the data collector for research purposes.)
No
b) Will the study require obtaining consent from a ”research participant
advocate” (for definition see guidance notes) in lieu of participants who are
unable to give informed consent? (e.g. for research involving children or, people
with learning or communication disabilities)
No
c) Will it be necessary for participants, whose consent to participate in the study
will be required, to take part without their knowledge at the time? (e.g. covert
observation using photography or video recording) No
d) Does the study involve deliberately misleading the participants? No
e) Will the study require discussion of sensitive topics that may cause distress
or embarrassment to the participant or potential risk of disclosure to the
researcher of criminal activity or child protection issues? (e.g. sexual activity,
criminal activity)
No
f) Are drugs, placebos or other substances (e.g. food substances, vitamins) to
be administered to the study participants or will the study involve invasive,
intrusive or potentially harmful procedures of any kind? No
g) Will samples (e.g. blood, DNA, tissue) be obtained from participants? No
h) Is pain or more than mild discomfort likely to result from the study? No
i) Could the study induce psychological stress or anxiety or cause harm or
negative consequences beyond the risks encountered in normal life? No
j) Will the study involve prolonged or repetitive testing? No
k) Will financial inducements (other than reasonable expenses and
compensation for time) be offered to participants? No
C2)
Yes or
No?
a) Will the study seek written, informed consent? Yes
b) Will participants be informed that their participation is voluntary? Yes
c) Will participants be informed that they are free to withdraw at any time? Yes
d) Will participants be informed of aspects relevant to their continued
participation in the study? Yes
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 77
e) Will participants’ data remain confidential? Yes
f) Will participants be debriefed? Yes
If you have answered ‘no’ to all items in SECTION C1 and ‘yes’ to all questions in SECTION C2 the
application will be processed through expedited review.
If you have answered “Yes” to one or more questions in Section C1, or “No” to one or more questions
in Section C2, but wish to apply for expedited review, please make the case below. See research
ethics website for an example “case for expedited review”.
C3) Case for Expedited Review – To be used if asking for expedited review despite answering
YES to questions in C1 or NO to answers in C2.
SECTION D - PARTICIPANT DETAILS
D1) How many participants will be recruited?
400
D2) How was the number of participants decided upon?
To calculate the sample size, the following calculation was undertaken, using
Statcal-EpiINFO Version 7.1; using the formula
(1.96 2*p(1-p))/e2
Where p=0.5 (50% - as there is no existing data) and e=0.05 (5%), the minimum
sample size required would be 384. Therefore 400 participants will be chosen from
the British born population within the east coast of England which has 6.5% non-UK
born population (Qpzm, 2012); ensuring there is an equal amount of male and female
participants, covering all adult age ranges.
D3)
a) Describe how potential participants in the study will be identified, approached
and recruited.
Stimuli participants’ recruitment
Stimuli participants used for the production of the stimuli will be recruited from a
pool of associates of the student researcher, approached through ‘Facebook-friends’.
Preliminary discussions have aided the researcher to identify the majority of the 12
different “speakers” required for the research. Upon receipt of ethical approval, a
voluntary invite shall be sent to all interested stimuli participants, explaining the
requirements and the purpose of the study in greater detail, seeking their official
permission to participate. Upon proposal acceptance, the male and female speakers
n/a
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 78
will be recruited for their anonymous assistance.
Upon agreement to continue and consent to use their voice for the study stimuli,
electronically signed through a tick-box; the speakers will be asked to read four short
sentences in their own language:- Chinese, Punjabi, Polish, Portuguese, Arabic and
English; both male and female, using a recording device with no background noise.
The stimuli participants will then email the voice sample to the student researcher.
This method is preferred and deemed to be most successful as the stimuli
participants are already aware of the Masters course undertaken and have previously
expressed interest in offering voluntary assistance when required. Furthermore, using
this method, the student researcher can request the same specific non-emotive
sentences for all languages.
Each stimuli participant used from the pool will be bilingual and fluent in both
English and their own native language, thus are able to translate the sentence
required properly into their natural native spoken language. Each speaker shall
record the following non-emotive sentence:
First you break an egg into a bowl. Then mix with sugar and add some milk.
After this, cover your baking tray with paper. Put the ingredients on the tray
and bake in the oven.”
The stimuli consisting of the six different languages in both male and female voices,
shall be uploaded to the wix hosting site and used within the survey questionnaire in
‘Qualtrics’ (Qualtrics, 2016). Each can be played by the participants prior to
answering the 7-item questionnaire for each voice.
Response participants’ recruitment
Research response participants will be recruited through online advertising within
social media applications ‘Facebook’ and ‘Twitter’ being the most popular amongst
the general population throughout the UK, and most likely to attract a UK wide
range of participants. A further recruitment method shall use online discussion
groups of the study and website within Liverpool University Laureate community.
Information will include the study’s purpose, inclusion and exclusion criteria,
proposed outcome and contact details for further information.
Participant recruitment will be on a voluntary basis and will continue until the
participant quota is fulfilled. Data will be collected through ‘Qualtrics’ (Qualtrics,
2016) with a link to a website hosted by wix.com which will hold all twelve voices,
being male and female speaking ‘Chinese, Polish, Punjabi, Arabic, Portuguese and
English’, chosen for being the languages most likely to be heard in the UK according
to the 2011 census (English – 1st most likely, Polish – 2nd , Punjabi – 3rd , Arabic –
7th , Chinese – 9th , Portuguese – 10th) (Evans, 2013). Participants will complete each
short 7-item questionnaire after listening to each voice.
Participants will be informed that all answers are confidential and only their gender
and age shall be recorded. They will be informed via a statement on the page leading
to the questionnaire that by clicking the ‘tick-box’, they are confirming they are UK-
born with a main language of English; agreeing to the instructions and that they
understand the purpose of the study, giving consent that their responses in the
research questionnaire be used as part of the study. For those who agree to continue,
survey questionnaires and voice links, together with information about the study will
be provided for potential participants.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 79
b) Inclusion criteria:
c) Exclusion criteria:
d) Are any specific groups to be excluded from this study? If so please list them
and explain why:
e) Give details for cases and controls separately if appropriate:
f) Give details of any advertisements:
All UK-born, British males and females between the ages of 18 and 80, with English as
their only, or main language. (Main is indicated as those English-born who can also speak
a second language i.e. French, German or another can be included within the study).
Any person who is not born in the UK and considered to be an ethnic minority with a
main language other than English.
Anyone UK-born who has a main language other than English.
Those who have received British citizenship yet were not born in the UK, using a main
language other than English, as they more likely to have a biased positive view of other
languages.
N/A
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 80
D4)
a) State the numbers of participants from any of the following vulnerable groups and
justify their inclusion
Children under 16 years of age: None
Adults with learning disabilities: None
Adults with dementia: None
Prisoners: None
Young Offenders: None
Adults who are unable to consent for
themselves:
None
Those who could be considered to have a
particularly dependent relationship with
the investigator, e.g. those in care homes,
students of the PI or Co-applicants:
None
Other vulnerable groups (please list): None
Online social media ‘Facebook’ advert amongst student researchers associates for
recruitment of stimuli participants and online advert on facebook and the University of
Liverpool community for recruitment of participants.
Stimuli recruitment advert
As a student of Liverpool University studying a Masters degree in Psychology, your
expert language skills are required for a dissertation study to better understand UK
attitudes towards other languages spoken in the UK.
You are asked to speak a few short sentences in your own language, showing no emotion,
with no background noise, into a recording device, to be emailed to myself, the student
researcher.
No personal information will be required from you and your contribution will be
anonymous, but greatly received.
The languages required, in both male and female voices are Polish, Chinese, Portuguese,
Punjabi, Arabic and English. If you are interested, please contact me at
markpsychologist@gmail.com for the specific sentences required.
Thank you for your assistance in this study.
Kind regards,
Mark A. Whittington-Buckley
Participant advert
You are invited to take part in an important study to better understand UK attitudes
towards other languages spoken within the UK. Your participation will be completely
anonymous and other than your age and gender, no other personal information will be
required. You will listen to 12 voices then register your opinion on a simple 7 question
questionnaire provided for each voice.
Thank you in advance for your participation and please enjoy the study and click the link
to continue.
SPOKEN LANGUAGE: UK ATTITUDES TOWARDS PEOPLE WHO SPEAK A
DIFFERENT LANGUAGE TO ENGLISH. 81
b) State the numbers of healthy volunteer participants:
Healthy Volunteers 400
D5)
a) Describe the arrangements for gaining informed consent from the research
participants.
b) If participants are to be recruited from any of the potentially vulnerable groups
listed above, give details of extra steps taken to assure their protection,
including arrangements to obtain consent from a legal, political or other
appropriate representative in addition to the consent of the participant (e.g. HM
Prison Service for research with young offenders, Head Teachers for research with
children etc.).
c) If participants might not adequately understand verbal explanations or written
information given in English, describe the arrangements for those participants
(e.g. translation, use of interpreters etc.)
d) Where informed consent is not to be obtained (including the deception of
participants) please explain why.
D6) What is the potential for benefit to research participants, if any?
Greater self-awareness of language diversity and better understanding of how
attitudes towards language can in be influenced simply by what is heard. Potentially
the research can aid the local councils and Communities and Local Government
department to create measures to help community cohesion and acceptance through
the UK.
A consent form attached to the online questionnaire will hold a ‘tick-box’ which
participants must click to agree to the terms of the study and that they freely volunteer
their participation. This box must be checked before being allowed to continue with the
study.
N/A
As participants are English speakers, I do not foresee a problem in this area. Should
participants require further details or clarification, they will be provided with an email
address in order to seek further information from the student researcher.
N/A
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DIFFERENT LANGUAGE TO ENGLISH. 82
D7) State any fees, reimbursements for time and inconvenience, or other forms of
compensation that individual research participants may receive. Include direct
payments, reimbursement of expenses or any other benefits of taking part in the
research?
None
SECTION E - RISKS AND THEIR MANAGEMENT
E1) Describe in detail the potential physical or psychological adverse effects, risks or
hazards (minimal, moderate, high or severe) of involvement in the research for
research participants.
None
E2) Explain how the potential benefits of the research outweigh any risks to the
participants.
Potential benefits involve self-awareness of attitudes and understanding British
attitudes towards other languages and whether it affects personal judgement of the
group speaking that language. This is important in order to introduce measures to
encourage acceptance within the UK and promote awareness and acceptance through
local and national government departments for communities.
E3) Describe in detail the potential adverse effects, risks or hazards (minimal, moderate,
high or severe) of involvement in the research for the researchers.
None
E4) Will individual or group interviews/questionnaires discuss any topics or issues that
might be sensitive, embarrassing or upsetting, or is it possible that criminal or other
disclosures requiring action could take place during the study (e.g. during
interviews/group discussions, or use of screening tests for drugs)?
YES NO X
If Yes, give details of procedures in place to deal with these issues.
N/A
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E5) Describe the measures in place in the event of any unexpected outcomes or adverse
events to participants arising from their involvement in the project
None as participants details are anonymous and confidential
E6) Explain how the conduct of the project will be monitored to ensure that it conforms
with the study plan and relevant University policies and guidance.
Besides the student researcher, the DA (Dissertation Advisor) will oversee the entire
project and ensure that it is in-line with the committee-approved study plan, as well
as University procedures and guidelines.
SECTION F - DATA ACCESS AND STORAGE
F1) Where the research involves any of the following activities at any stage (including
identification of potential research participants), state what measures have been put in
place to ensure confidentiality of personal data (e.g. encryption or other anonymisation
procedures will be used)
Electronic transfer of data by magnetic or
optical media, e-mail or computer
networks
Data shall be collected from Qualtrics
online survey. Participants are not
required to submit any personal
information, so their anonymity is
protected.
Sharing of data with other organisations Data information shared with local
government (Norfolk Council Council
and with national government
(department of Communities and Local
Government); to be made aware of public
attitudes to language, in order to
introduce awareness schemes to improve
community adhesion. However all
participants data to remain confidential.
Export of data outside the European
Union
N/A
Use of personal addresses, postcodes,
faxes, e-mails or telephone numbers
None
Publication of direct quotations from
respondents
None
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DIFFERENT LANGUAGE TO ENGLISH. 84
Publication of data that might allow
identification of individuals
None
Use of audio/visual recording devices Computer recording device used to
record stimuli participants language only,
for use within the study. Stimuli
participants identity to remain
anonymous.
Storage of personal data on any of the
following:
     
Manual files None
Home or other personal computers Information held for 5 years after the
study’s end.
University computers Information held for 5 years after the
study’s end.
Private company computers None
Laptop computers None
F2) Who will have control of and act as the custodian for the data generated by the study?
Student researcher, DA and DoS
F3) Who will have access to the data generated by the study?
Student researcher, DA and DoS
F4) For how long will data from the study be stored?
5 years
SECTION G – PEER REVIEW
G1)
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DIFFERENT LANGUAGE TO ENGLISH. 85
a) Has the project undergone peer review?
YES X NO
b) If yes, by whom was this carried out? (please enclose evidence if available)
SECTION G - CHECKLIST OF ENCLOSURES
Study Plan / Protocol x
Recruitment advertisement x
Participant information sheet x
Participant Consent form x
Research Participant Advocate Consent form x
Evidence of external approvals x
Questionnaires on sensitive topics x
Interview schedule n/a
Debriefing material x
Other (please specify) n/a
Dissertation Advisor:- Stamatis Eldib
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