Differences in Applying the Terms “Sex” and “Gender” Across Scientific Authors Active in English and Non-English Speaking Countries

THE TERMS “SEX” AND

“GENDER” ACROSS SCIENTIFIC AUTHORS ACTIVE IN ENGLISH AND NON-ENGLISH SPEAKING

COUNTRIES

Rebecca Eriksson

Bachelor’s thesis, 15 ECTS

Bachelor programme in Cognitive Science, 180 ECTS Spring term 2021

Supervisor: Guy Madison

guidance throughout this process, around the clock. I am also thankful for

my family and friends for always being my greatest cheerleaders.

Abstract

The aim of this present study was to examine whether scientific authors active in English-speaking countries differ from those in non-English-speaking countries in their use of the terms ‘sex’ and ‘gender’. Based on earlier science, findings have shown that the first language (L1) and second language (L2) differ in the neural processes of the brain and working memory. Research has also shown that women tend to communicate in a more polite and involved manner compared to men. Based on such findings, we compare authors’

tendency to use the terms sex and gender correctly, as a function of their sex and whether they were affiliated to a country with English as first language (EFL) or English as second language (ESL). The hypothesises of this study were (1) scientists affiliated to universities located in EFL countries are more likely to use the terms sex and gender correctly, compared to scientists affiliated to universities in ESL countries, and (2) female scientists are more likely to use the term gender, when they are actually referring to sex, than male scientists and are also less likely to use the term sex when they are referring to gender, compared to male scientists. Results supported the first but not the second hypothesis. Further results are analyzed and discussed based on theories from cognitive science.

Keywords: cognitive science, sex, gender, sex differences, language, English Sammanfattning

Syftet med denna studie var att undersöka om vetenskapliga författare som är verksamma i engelsktalande länder skiljer sig från dem i icke-engelsktalande länder när det gäller att använda de engelska termerna ”sex” och ”gender”. Baserat på tidigare vetenskap har fynd visat att första språket (L1) och andraspråket (L2) skiljer sig åt i arbetsminne och hjärnans neurala processer. Forskning har också visat att kvinnor tenderar att kommunicera på ett mer artigt och involverat sätt jämfört med män. Baserat på sådana resultat jämför vi författarnas tendens att använda termerna kön och kön korrekt, som en funktion av deras kön och om de var affilierade till ett land med engelska som första språk (EFL) eller engelska som andraspråk (ESL). Hypoteser i denna studie var (1) forskare som är anslutna till universitet i EFL-länder är mer benägna att använda termerna kön och kön korrekt, jämfört med forskare som är anslutna till universitet i ESL-länder, och (2) kvinnliga forskare är mer benägna att använda begreppet gender, när de faktiskt menar sex, än manliga forskare och är också mindre benägna att använda termen sex när de menar gender, jämfört med manliga forskare.

Resultaten stödde den första men inte den andra hypotesen. Ytterligare resultat analyseras och diskuteras utifrån teorier från kognitionsvetenskap.

Nyckelord: kognitionsvetenskap, språk, lingvistik, engelska, könsskillnader

Differences in Applying the Terms “Sex” and “Gender” Across Scientific Authors Active in English and Non-English Speaking Countries

Language is a complex and cognitively demanding task, specific for the human race.

However, any healthy individual that is exposed to an unspecified language before puberty, also known as “the critical period”, possesses the ability to acquire said language and learn it’s syntactical structure and grammatical rules by heart (Penfield & Roberts, 1959). Due to this natural predisposition, language is considered a “human universal”.

In today’s global society the acquisition of multiple languages is no rare occurrence, no matter the individual’s mother tongue or first language (L1). English has grown into one of the most prominent second languages (L2) around the world and is increasing within the scientific community (Moskaleva & Akoev, 2018). Even though academics’ skills in English as a second language are exquisite, research has shown that second language speakers can rarely compete with a native speaker of the same language, even though the native speaker may have fewer years of experience with said language (Hinkel, 2003).

Consistent with a critical period, it has been shown that L2 acquired later in life recruits and activates different, and larger areas of the human brain compared to L1 (Liu &

Cao, 2016). If the L2, however, is acquired earlier in childhood, an activation pattern similar to that of an L1 can be seen. Due to this, it is assumed that usage of an L2 acquired later in life is considered to be more demanding compared to L1 usage. It has also been shown that bilinguals (or multilinguals) differ from monolinguals of the same language. Is it due to the fact that bilinguals are directly or indirectly influenced by their other language(s) (Kaufmann, 2019).

Earlier research on “study abroad”-students has revealed that students that spent an extended amount of time in a country whose native language is the same as the student’s L2 tend to increase their L2 skills more than their peers that did not study abroad (Baker-Smemoe, Dewey, Bown & Martinsen, 2014; Leonard & Shea, 2017). It is assumed that the interaction with native speakers and the increased, natural exposure to one’s L2 has positive effects on L2 learning, which can be hard to replicate in a classroom setting (Leonard

& Shea, 2017).

During the course of their extensive training/education, academics and scientists are assumed to have a high level knowledge of English grammar and syntax, especially if they have been affiliated to a university within an English-speaking country for some time.

However, there are more subtle levels of language comprehension and usage which may be of importance in regards to scientific communication. Hence, scientists located in countries with English as first language (EFL) should have a greater English comprehension, regardless of their actual L1, compared to scientists located in countries with English as second language (ESL). To examine this I will look into whether the usage of English concepts differ between scientists of different affiliations. To examplify this, I will estimate how well they use the terms sex and gender.

Sex and gender are frequently mentioned and used as variables in the extensive

litterature on individual differences in cognitive function, because systematic differences

between the sexes are very commonly found. A lot of this science use the naturally occuring sex and gender differences to compare hypotheses based on widely differing perspectives, like biological, evolutionary and socio-psychological theories (i.e. Archer, 2006; Miller &

Halpern, 2014; Wood & Eagly, 2002). Since sex can have different meanings depending on the situtation, the academic litterature have moved towards using the concept of gender to represent the social aspects of sex. This may include clothing, ornaments and certain kinds of behaviors that may be socially or culturally conditioned. Some researchers claims that even some interests, preferences and skills are learned to a significant degree due to the individual adopting and internalizing social norms manifested in other people (i.e. Ledin, Bornmann, Gannon & Wallon, 2007). According to this logic the concept of sex represents the aspects related to biological sex. Since sex and/or gender is a common variable in scientific studies, it is of utmost importance that these concepts are differentiated and used in a correct way to avoid unnecessary confusion (Prince, 1985).

There are, however, indications that this differentiation is not maintained (Haig, 2004). According to Prince (1985) many textbooks start out with a clear definition of sex and gender respectively, and yet the authors tend to use them incorrectly later on. The meaning of words, terms and concepts plays a vital part in communication between people, regardless of whether it occurs orally or in writing. It is of utmost importance that the listener or reader understands the meaning of what one wishes to convey with as little ambiguity as possible.

The main question of this study is to examine to what extent and how well scientific papers make the distinction between sex and gender, e.g. that sex really is used to describe biological sex, because it is the actual variable measured or that is relevant to the theories presented in the study. In the same way gender should be used to describe the social aspects of sex, when these are relevent for the research.

Hence, it is relevant for this current study to explore some of the ways men and women systematically differ in regard to expressing themselves verbally or in writing (cf.

Wallentin, 2009). Coates (2004) referres to earlier research on oral conversations in same-sex group settings, e.g. women or men exclusively. In these settings there are clear distinctions to the ways which women and men speak. For instance, linguists classify women’s speech style as “cooperative” and “polite”, while men’s speech is seen as “competitive”. However, spoken language contains a lot more than just plain words. There are almost an endless amount of variables to take into account, i.e. voice pitch, intonation, body language and social cues. It is a fair assumption that these variables present in oral conversations may be the reason for the differences in female and male speech. One way to reduce the amount of uncontrollable variables is to analyze written texts instead.

Afterall, written texts are usually aimed towards a broader and, more or less, unknown

audience. They also lack the complexity of phonology and intonation, where differences in

male and female speech have been found. Due to this, Argamon and colleagues (Argamon,

Koppel, Fine & Shimoni, 2003) discussed how earlier research made the assumption that

formal, written texts shouldn’t give rise to any, or at least fewer, differences in writing style

between men and women, compared to speech. Argamon et al. (2003) did however discover

systematic differences between male and female formal text authors. Some of the research

findings were that women tend to use more pronouns and use a writing style that linguists call

“involved”. Involved writing is characterized by using first and second person pronouns, which creates an interaction between the author and their reader. Instead, men have a writing style described as “informational”, since they tend to indicate or specify what they write about to a greater extent.

In this current study, the main hypothesis is that (1) scientists affiliated to universities located in EFL countries (e.g. the US, Great Britain, Canada etc.) are more likely to use the terms sex and gender correctly, compared to scientists affiliated to universities in ESL countries. As a control variable I will take the scientist’s sex into account, and based on earlier finding that women tend to value social relations, and that gender describes social aspects of an invididual, I’ll therefore post the hypothesis that (2) female scientists are more likely to use the term gender, when they are acutally referring to sex, than male scientists and are also less likely to use the term sex when they are referring to gender, compared to male scientists. If both of these hypotheses are confirmed, there is likely an interaction between the affiliation and sex of the scientist, which will be analyzed specifically in that case.

Method Instruments and Materials

The main data required for this study consisted of the meaning applied to the terms ‘sex’ and

‘gender’ in scientific articles related to sex differences, the sex of the authors as these articles, and their likely native language, as inferred from the counry of their affiliation. To this end, a large sample of articles were scrutinized for these data, as described below.

Data Set

The data set used in this study consisted of 610 articles published in scientific journals between 1973 and 2014. All articles were gathered through a systematic search in several databases to find research on human psychological sex and/or gender differences.

Specifically, these articles were compiled as the basis for three meta-analysis of sex differences in episodic memory (Asperholm et al., 2019; 2020; 2020). Thus, the articles are mainly derived from the field of cognitive psychology extending into neuroscience. An automated routine determined the number of occurence of the terms sex and gender, separately for the title, abstract and the body of the text, and an ID number matched to the name of each article in PDF format.

The articles were compiled in two sets, one covering the period 1976-2014 (N = 138) and the other 2001-2014 (N = 465). Of the total of 610 articles in the data set, the full-text PDF could not be obtained for seven articles. The coding could not be finished in time by the current author, so when the newer articles were completed, the older ones were randomly ordered and 53 of them coded (thus excluding 85 articles). Five articles were also excluded due to either being unsearchable with the inbuilt search tool of the PDF readers (N = 3) or not containing either the term sex or gender (N = 2).

Thus, a final data set of 514 articles were coded and analyzed for this study.

Data Collection and Ratings

The data collection and ratings were based upon several variables.

Sex of the Authors. Sex was coded as uncertain (0), male (1) and female (2). In most cases, the authors’ sex was determined by their first names. If the first name was ambiguous or from a cultural region whose name-sex association the current author was unfamiliar with, an online search was performed for the full name, which usually resulted in profiles with portrait pictures of the author. In the cases where no useful information could be found sex was coded as “uncertain”. Several articles provided only initials for the authors’ first name. In cases where extended searches on the journal’s websites, academic databases, or the Internet generally did not reveal the author’s first name these authors were also coded as “uncertain”

with regard to sex. When the number of authors (N) were more than 12 for a single paper, author(s) 12 through N-1 were excluded. Thus, I included the 11 first authors and the last author (in these cases marked as the 12th author).

Affiliation. The country of the first two authors’ affiliation(s) were controlled. This was coded as affiliated in an ESL country (0), affiliated in an EFL country (1), and affiliated to both ESL and EFL countries (2). Countries which were considered to have English as their primary language were: the United States, Canada, the United Kingdoms, Ireland, Australia and New Zealand. Other countries with English as the official, primary language were not represented in the current sample and therefore not taken into account. The remaining countries, besides those mentioned previously, were coded as ESL.

Participant Labels. Data was collected on what label(s) the authors’ used to describe their study participants. Each label pair (men/women, male/female, boy/girl) was set as their own variable and coded as either not used (0) or used (1). Labels were only coded as being used if they occured in the context of describing the participants of the actual study. Labels used to make references to earlier research were not taken into account.

Source. If, and how, the authors had provided information on how the variables sex and/or gender of the participants were determined. The source of information for the variables sex and/or gender of study subjects were mainly gathered from the “methods” part of the report. This variable was dummy coded as no information provided (0), reported by authors as binary labels without support (2), self-reported with binary labels (3), visual inspection (7), biomarker (e.g. genes, hormones, anthropometry, voice pitch, pregnancy) (10), combination self-report and records (11), without support combined with menstrual cycle control (12), self-reported through force choice binary labels (13), and not relevant for this study (99). In cases of which there was no explicit information on how this data was gathered and determined, yet the authors used any of the previously mentioned binary labels, the article source was coded as reported as binary labels without support. If, and only if, the report didn’t use any participant labels nor provided the reader with any information on data gathering of the sex/gender variable, the article was deemed as no information (1).

Usage of Sex and Gender. The rating of whether the terms sex and gender were used

correctly in both abstract and body text was based on several factors: 1) the context of where

they appeared, 2) whether the authors had provided sufficient information regarding the

variables, i.e. the rating of the “source” variable mentioned above, 3) whether they were

using the terms interchangeably or not, and 4) the hypothesis and aim of the study, i.e. if it

was relevant for the study to examine the variable(s) sex and/or gender, respectively. These factors were weighed more or less for the rating depending on the specific study. The variable was coded as N/A (i.e. not available) (0), incorrect usage (1), correct usage (2), uncertain (3) and both correct and incorrect use (4). There were some articles where the terms sex and gender had a different meaning than the one that was aimed to analyze in this paper. If an author used a term exclusively to refer to other meanings of sex or gender, these occurrances was coded as 0 = N/A as well.

Analysis

Data analysis was conducted with the open source statistical tool JASP 0.14.1 and SPSS to extract frequencies for each correct and incorrect use of each term, based on author affiliation and sex. These frequencies were further used to make Chi-squared tests using Microsoft Excel and Google Sheets. The variables used for analysis were sex and affiliation for both first and second author respectively. Correct and incorrect usage of the terms sex and gender were then compared to the author variables. The new and old sample was analyzed separately and merged to detect any significant differences between the samples. Since no major differences could be detected between the samples, all analyses were conducted on the merged samples.

Procedure

Each article was viewed in full text in a suitable PDF reader. For each article, the inbuilt search tool of the PDF reader was used to find the following terms: sex, gender, wom(en), (fe)male, boy and girl. For each search term, data was collected and compiled in an online spreadsheet using Google Drive.

Most of the data gathering was based on the paragraphs and sentences where the search terms were found. In some cases, sufficient information could not be collected solely by reading the sentences and paragraphs around each search term. For these articles a greater part had to be read and/or skimmed through to gain a proper understanding before rating.

Information of what labels the authors had been using for the participants were usually the first step of the rating process. Information on labels was mainly extracted from the “methods” section of the paper, as well as the rating of “source” that was usually determined next.

Next, the rating of whether the terms sex and gender were used correctly were assessed. This data was mostly based on the abstract, methods and discussion parts. The introduction and results were also considered, but these pasts usually contained the terms as references to earlier research and/or recurring variable names. Hence, these specific occurrences were not considered for the overall assessment of the authors’ usage of the terms.

The reason for excluding these occurrences was due to not being able to control whether the

authors’ were referring to other researchers correctly. Also, a recurring variable name

including the term sex and/or gender was assumed to have a set meaning through-out the

paper.

Information regarding the authors’ sex and affiliation were mainly performed at a different point in time compared to the rating of the article or after the rating of the article was complete. This was done to reduce bias as well as possible.

Once the data gathering was complete, the data file was exported and analysed with the tools mentioned previously.

Results

Descriptive statistics of the authors’ demographic data are reported in Table 1. An independent samples t-test indicated no significant differences between first and second authors’ sex (p >.05). However, the independent samples t-test showed a significant difference between affiliation of first and second authors (p <.001).

Table 1

Descriptive statistics of complete data set

Sex M/F EFL ESL Both EFL and ESL

First author 211/252 277 234 3

Second author 211/223 262 229 0

Missing data 108 0 0 0

Note. Total data set consisted of N = 514 articles. M = male, F = female. EFL = English as a first language, ESL = English as a second language.

Chi-square tests for independence were conducted on the terms sex and gender as a function of the sex and the affiliation of the first and second author. Most results were non-significant (p >.05), among which were author’s sex to either term, as well as the use of the term sex for either author and their sex or affiliation.

However, some significant results were obtained. When comparing usage of the term gender in relation to author affiliation, significant results were found for both first authors, X

(1) = 4.9, p < .05 and second authors, X

(1) = 4.1, p < .05. Authors within EFL countries were significantly better at using the term gender correctly compared to authors within ESL countries. First and second authors of the same affiliation scored the same percentage and are presented together in Figure 1. The correct usage of the term gender was, however, quite poor for this specific sample generally.

The use of the term sex was never coded as incorrect throughout the whole sample,

but there were a few occurrences of them being coded as uncertain or as both correct and

incorrect. The frequencies of total occurrances for each term in relation to author sex and

affiliation can be seen in Table 2 and 3 respectively.

Table 2

Frequencies for each term based on sex of first author

Sex term Gender term

Male first authors 130 105

Female first authors 155 126

Total 285 231

Note. No occurrences of sex were coded as incorrect.

Table 3

Frequencies for each term based on affiliation of first author

Sex term Gender term

First authors in EFL countries 177 132

First authors in ESL countries 142 122

Total 319 144

Note. No occurrences of sex were coded as incorrect. EFL = English as a first language, ESL

= English as a second language.

Generation of a sexscore based on the quota of all article authors’ sex (up to 12

authors) was established. The sexscore was used to compare usage of the term gender. The

results of this analysis showed that the sexscore was more female (1.63) for correct use of

gender and more male reliant for incorrect usage (1.49), indicating a small to medium effect

size (d = 0.42). In Figure 1, the overall use of the term gender for first and second authors

based on affiliation is shown. Since no occurrences of the term sex was coded as incorrect,

the need for plotting this data was not thought to be necessary.

Figure 1

Authors’ use of the term gender based on affiliation

Note. a) First and second authors within EFL countries, b) first and second authors within ESL countries.

Discussion

The main hypothesis of this paper was to examine if there are any differences between authors affiliated to EFL and ESL countries. Since there are no observed cases of incorrect usage of the term sex in the analyzed sample, no conclusions can be drawn from this term specifically. This leaves us with the well debated term gender. The coding for whether gender is used correctly or not is based on the definitions stated earlier in this report. Briefly, gender is to be used to describe social aspects traditionally associated with the different sexes, such as behaviours.

As mentioned in the results, there is a significant difference in the correct usage of the

term gender. Even if the results are overall poor for correct usage of the term, authors within

EFL countries perform twice as good on correct gender use, compared to ESL authors. Based

on the method in this study, it can not be concluded with certainty that each author’s first and

second language is coherent with their country of affiliation. Nonetheless, these results do

provide some support for earlier research stating an increase in second language skill for

students that study abroad for an extended period of time within a country whose primary

language is coherent with the student’s L2. Thus, it is also assumed, based on the findings in

this article, that the authors’ that originate from an ESL country benefit on some levels in

language comprehension and usage, thanks to their affiliation in an EFL country. However,

the exact distribution of the authors’ first and second languages are unfortunately not known

for this sample. The collection of this precise language data would take too long to collect

and compile to match the time frame of this current study. It is of course possible, however

unlikely, that the majority of authors affiliated to an EFL country don't have it as their L1 as

well. Hence, for this study it is assumed that most of the authors are affiliated to their country

of origin, mostly based on the authors’ names being coherent with the culture of the country

of affiliation. Based on this assumption, there is some support for cognitive theories and

findings from earlier research on this topic.

In 1996 Kellogg proposed a model of working memory (WM) in regard to writing, based on the original WM model laid out by Alan Baddeley (Baddeley, 1986; Kellogg, 1996).

Many of its core predictions are still supported many years later (Kellogg et al., 2013).

Kellogg and colleagues (2013) have even proposed that writing is “as much a thinking task as it is a language task” due to the complexities and restrictions of written communication, compared to speech. It is therefore likely that even more complexity is obtained during formal writing of scientific literature, such as the data studied in the current paper. A lot of research has since been conducted to examine the WM processes and neural mechanisms of writing. As mentioned in the introduction, it has been reported that the human brain shows different activational patterns depending on whether a person is using their first or second language, especially if the L2 is acquired later in life (Liu & Cao, 2016). Based on this, it is assumed that L2 usage is more demanding compared to L1 usage.

Research has also shown that there are certain differences between writers in their L1 and L2. Among some of the findings, L2 writers tend to pay more attention to low-level linguistic aspects (e.g. spelling) compared to L1 writers (Whalen & Ménard, 1995). For L1 writers, on the other hand, spelling is more of an automated process, leading them to focus more on high-level aspects of writing such as pragmatics. Other researchers have found evidence of differences in working memory for L1 and L2 writers where L1 writers tend to rely more on the phonological WM compared to L2 writers, who are more reliant on visual processing (Gunnarsson-Largy, Dherbey & Largy, 2019). However, according to Gunnarsson-Largy and colleagues, L2 writers who are more advanced, a progression towards a greater reliance on phonological WM have been noted as well, as seen in L1 writers. These findings go hand in hand with the results reported in this study due to chunking authors’ by affiliation country instead of actual L1 and L2. Hence, the results of this current research provide evidence of a significant difference in term usage between EFL and ESL country authors. This can possibly imply a subtle yet existing difference in language comprehension and usage based on disparities of the neural processing of the working memory of L1 and L2 usage respectively.

However, the analysis shows no support for the second hypothesis of this study that

female authors would use the incorrect term gender instead of sex, in the cases where this is

what is actually measured. Conversely, there are instead some indications that correct use of

the term gender has a female dominant sexscore, and incorrect use tends to be more male

dominant. As previously stated, there have been some findings that men and women do

differ in both speech and writing style (Argamon et al., 2003; Coates, 2004). It has been

noted that women have a more involved and polite way of communicating. However,

research on human sex differences over the years have also found that women generally

perform slightly better on verbal tasks compared to men (Halpern et al., 2007). Due to this, it

is possible that women's polite communication style and their advantage in verbal abilities

out-weigh each other, at least in the formal settings examined in this study. It is possible that

women overall have a better understanding of the term gender, thus performing better at

using the term correctly. However, the sample and terms examined might not be optimal to

make a definite assumption regarding sex differences in term usage just yet. The data set was

mainly based on research in the field of cognitive psychology, expanding into neuroscience.

Thus, a rather homogeneus sample with a bias towards sex being the correct term of use. For future research it might be wise to compare a larger data set, including other research fields, to be able to draw better conclusions regarding sex differences in scientific authors use of certain terms.

During the data collection process it was judged to be both necessary and interesting to collect some extra data, compared to the original plan. The hope was to gain a clearer understanding of the articles, and by extension, make a sensible rating of the content of the article. It was also expected to find some further differences and similarities between authors with the help of this extra information. However, there was not sufficient time to analyze all of the collected variables, which might have provided an additional layer to this study. Due to the current author’s lack of knowledge in detecting sex based on names of certain cultural regions, there is some amount of missing data on the sample data authors’ sex. It is therefore possible that there is a bias in the sex variable used for measures in this study.

It was clear that most articles lacked a proper description of how the data on

participant sex and/or gender had been collected. It was quite obvious early on in the rating

process that it was implied that sex and/or gender is a self-explanatory variable compared to

other measurements. Authors were usually quite expressive when accounting for how other

variables had been collected, yet leaving out the details on how they had gathered

information on participant sex and/or gender, mostly leaving the reader guessing. In

extension, this made the rating process of the source variable, as well as the determination of

whether the author used the terms examined in this paper correctly or not, a whole lot

trickier. Ninety percent of the articles provided no support for their sex and/or gender

variables, yet used binary labels (i.e. men/women, male/female etc.) to describe participants

of the study. During data collection, it was clear that many authors, regardless of affiliation,

used the term gender interchangeably with sex even though they have distinct differences in

meaning. As discussed by earlier scientists (Kellogg et al., 2013; Prince, 1985), the need for

unambiguous communication in writing is of the essence. This is especially true in the realm

of scientific literature. It is therefore astonishing after this data analysis to see so many

scientific authors writing of the need to provide sufficient information of the measured

variables sex and gender. It is according to the author of this paper likely that many scientists

see these variables as self-explanatory, negating the need for support of how this data is

collected and in extension, how the terms are being used.

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