A Neuroscientist Wonders Aloud – what IS gender?
A Neuroscientist Wonders Aloud – what IS gender?
By Gina Rippon
Professor Gina Rippon is an international expert on brain-imaging techniques, and Emeritus Professor of Cognitive Neuroimaging at the Aston Brain Centre, Aston University, Birmingham UK. She has a PhD in Psychophysiology from the University of London, and has held full-time research and teaching positions at the University of Warwick and at Aston University, as well as honorary positions at Imperial College, London; University of Wisconsin, Madison, USA and Macquarie University, Sydney, Australia. She is a Chartered member of the British Psychology Society and has served as President of the British Psychophysiology Society (now the British Association of Cognitive Neuroscience). In 2015, she was made an Honorary Fellow of the British Science Association for services to science communication.
Professor Rippon is an outspoken critic of “neurotrash,” the populist (mis)use of neuroscience research to (mis)represent understanding of the brain and, most particularly, to prop up outdated stereotypes. In her book ‘The Gendered Brain’ (Bodley Head - UK edition), 'Gender and our Brains' (US edition), she challenges the idea that there are two sorts of ‘hardwired’ brains, male and female, and offers a 21st century model for a better understanding of how brains get to be different. Her latest book, coming out in 2025, is The Lost Girls of Autism: How Science failed autistic women – and the New Research that’s Changing the Story. (UK) / Off the Spectrum: Why the Science of Autism has failed Women and Girls (US).
“When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to mean—neither more nor less.”[1]
— Lewis Carroll
I have found this Humpty Dumpty test a useful filter when I come across a widely discussed variable in research about which there is an illusion of consensus. As ‘everybody knows’ what Factor Y is, you don’t need to clarify in detail what it actually is (or acknowledge that it might mean different things to different people), you just need to firmly state what test you were using to measure it and use the resulting score to back up whatever argument it is that you are making. Historically, I think this was applied to the use of IQ as an independent variable; I have just been making the case that the same goes for autism [2]; and I firmly believe that this is what is going on in research into ‘gender’. We might have moved beyond the days where the terms ‘sex’ and ‘gender’ were used interchangeably (or where, indeed, ‘sex’ was the only term being used), but that does not seem to be because we are now all agreed on what each of these terms mean. Recently, there is welcome evidence of rigorous attention being paid to the nuances of what is meant by “sex” [3]; there is much less evidence of this in considering what is meant by ‘gender’.
I have just been wrestling with an influx of requests from science journalists to comment on preprints or embargoed papers on the latest “At Last the Truth” neuroscience research findings. The female/male brain crusade seems to have gone down a new rabbit hole (apologies for another Lewis Carroll reference). Along with the potential for harnessing machine learning techniques to winkle out those darned elusive sex differences (a thought for another day), it appears that neuroscience has discovered ‘gender’. Or, more particularly, mainstream and social media journalists have started to notice that ‘gender differences’ might be a more catchy hook for their next, ‘what’s new in brain research’ column.
The particular paper that started my ‘gender musings’ was a study of connection pathways in children’s brains [4]. Using machine-learning techniques to interrogate data from over 4K children (aged 9-10), from the ongoing Adolescent Brain Cognitive Development (ABCD) study [5], the authors investigated the association between measures of brain functional connectivity and Sex (as assigned at birth) and Gender (both self- and parent-reported). Finding different networks statistically associated with Sex and (parent-reported) Gender, the authors claimed, “in children, sex and gender are uniquely reflected in the intrinsic functional connectivity of the brain”
There were all sorts of issues with this paper. They were sufficient to convince me to persuade the science journalist who had approached me not to cover it. But many of the email exchanges leading up to this decision concerned “gender”. I had earnestly informed them: “the definition and operationalisation of gender is very poor”. To which the (perfectly correct) response was along the lines of “so what is gender then and how do you measure it?”
To be fair, the authors of this paper had acknowledged this conundrum: “Gender is a multidimensional construct that encompasses an individual’s internal identity, and their external interactions and behaviours, both of which are extremely difficult to quantify (own emphases) “
So what was their choice of gender quantification? With respect to the children themselves, it was mainly a measure of “gender contentedness”. Girls/boys were asked questions such as “How much do you feel like a girl/boy” or “How much have you had the wish to be a boy/girl?” With respect to their parents, the questions were focussed on ‘gender conformity’ (with the questions themselves revealing powerfully stereotyped assumptions): “He plays with girl-type (sic) dolls, such as Barbie”. Or “She plays “girl-type” games (as compared to “boy-type” games).” The ratings on these measures were reduced to a single numerical score. These were the measures, then, that the researchers claimed could “uniquely” be linked to specific functional networks in the brain by their machine-learning model of choice. (I am deliberately repeating their use of the word “uniquely” as I, in my non-machine learning way, predicted that this would be exactly the right headline-capturing term to ensure this paper got widespread coverage beyond the pages of its research journal (another thought for another day, perhaps [6]).
As, indeed, it did. My inbox filled up with Google alerts and Eureka alerts – some from the usual more murky waters of science communication, but some linked to more august outlets such as Science, New Scientist and Scientific American. Headlines such as “Neuroscientists reveal key brain differences between sex and gender” “Sex and Gender Operate Differently in The Brain” “Sex and gender map onto Different Brain Networks in Children” accompanied pieces inferring that, at last (own emphasis), brain researchers were waking up to the fact that this thing called ‘gender’ might impact the brain differently from that other thing called ‘sex’.
One well-known neuroscientist exclaimed, “I don’t think anyone’s looked at this question of how brain networks are related to sex versus how they are related to gender……Many previous studies just never bothered to ask about gender”. One of the authors was quoted as saying “ It’s becoming more and more clear that just looking at sex itself is not enough…It’s not going to give us all the answers”.
Very few of the articles identified how gender had been measured, and not one queried whether the one used was an appropriate measure or not.
Many of you may already be spluttering that many branches of research have been pursuing a gender agenda for many years, if not decades. Indeed (full disclosure), I and a group of like-minded colleagues wrote a paper TEN YEARS AGO, urging researchers in our field to pay more attention to the effects of “gender” in researching differences between the brains of females and the brains of males [7].
But to be fair, have we been falling into the Humpty Dumpty trap of using the term ‘gender’ to mean what we want it to mean, without being a bit more up front about what ‘it’ actually is?
There are, of course, many definitions of gender, as in the paper above. Some are the result of very high-level discussions and debates; The World Health Organization (WHO) defines gender as “the characteristics of women, men, girls and boys that are socially constructed. This includes norms, behaviours and roles associated with being a woman, man, girl or boy, as well as relationships with each other. As a social construct, gender varies from society to society and can change over time.” (WHO) Almost all the definitions include the term “multifaceted” or “multidimensional” or “multifactorial”. The term “umbrella concept” often pops up (meaning all-embracing - or covering a multitude of sins?!)
But it is when you start to look at how such definitions are operationalised, what measure of this ‘multi-faceted concept’ researchers choose in exploring gender, that you get to see Humpty Dumpty at work.
In some research spheres, gender is a psychological variable, along the lines of an individual personality characteristic. Dimensions such as ‘masculinity or femininity’ are often referred to. ‘Gender’ may be couched in term of identity: “a person’s identification with cultural definitions of being female or male or typically masculine or feminine attributes” [8]. It may be measured by self-report or by observations of (say) parents or caregivers. There are many measures of this aspect of gender out there; a recent systematic review identified twenty-nine different instruments [9]. No-one has yet done a validity assessment to test the extent of agreement between so many different measures. A recent paper by Julia Rauch and Lise Eliot explored how this approach is playing out in the human brain imaging field [10]. This included a helpful review of the various measures being used, including the new Gender-Related Attributes Survey (GERAS) [8]). So this approach to gender implies an independent variable, to be measured in individual participants – Rauch and Eliot’s review suggested that it was early days yet, but certainly indicated that there are better ways of operationalising gender than had been employed by the connectivity paper that had kicked off my musings.
But another approach to gender is that it is more of a dependent variable, the outcome of external influences. This has been dubbed the ‘Gender as a Sociocultural Variable’ approach [11] to complement the ‘Sex as a Biological Variable’ policy in relevant research fields [12]. The focus is more on so-called “gender-related” variables – here gender refers to “sociocultural factors that shape the identities, attitudes, behaviours, bodily appearances, and habits of women, men and gender diverse individuals”. A questionnaire has been developed for measuring “gender-related variables for health research”, which identifies core gendered external variables such as “caregiver strain” or “social support”. This use of gender is characteristic in health research, where the focus is on those social or cultural factors that need to be accounted for in explaining individual differences in health outcomes and disease processes.
Here we seem to have two approaches to what gender means, which could perpetuate the traditional either/or nature/nurture debate. Gender is something you are, or gender is something that is done to you? Both seem to miss the definition that I and my colleagues were trying to articulate ten years ago, that gender is inextricably entangled with biological sex [13]. Surely, what we now know about the lifelong plasticity of the human brain means that any definition of gender should acknowledge the dynamic and continuous interactions between Gender as a Psychological Variable and Gender as a Sociocultural Variable – Gender as a Biocultural Variable, perhaps? This has been articulated at a conceptual level [14] and also at an empirical level, via the application of social neuroscience models [15]. So we could have a third category of meanings for gender?
Back to Humpty Dumpty then. In response to his (?) assertion about word use, Alice observed: “The question is…..whether you can make words mean so many different things”. When it comes to understanding “gender”, it seems that it can mean so many different things. But we do need to be aware of this, in understanding what any kind of “gender” research is actually measuring. As brain scientists, we need to know if the use of careless definitions of gender, or poorly operationalised measures, could add fuel to gender essentialist fires. Speaking as someone whose work has been described as “smacking of feminism with an equality fetish”, I know the importance of needing to be very clear about what I am measuring and why I am measuring it!
My apologies to readers of the World Without Gender that my thoughts here have been all about gender! Perhaps you could let me know your thoughts and tell me if, Alice-like, I have just disappeared down a non-existent rabbit hole. And, ideally, how I might get out again.
References
Carroll, L. (1872). Through the Looking Glass, and what Alice found there. Macmillan, UK.
Rippon, G. (2025). The Lost Girls of Autism: How Science failed autistic women – and the New Research that’s Changing the Story. Macmillan, UK; Off the Spectrum: Why the Science of Autism has failed Women and Girls. Seal Press, Hachette Book Group, US.
Pape, M., Miyagi, M., Ritz, S.A., Boulicault, M., Richardson, S.S. and Maney, D.L., 2024. Sex contextualism in laboratory research: enhancing rigor and precision in the study of sex-related variables. Cell, 187(6), pp.1316-1326.
Dhamala, E., Bassett, D.S., Yeo, B.T. and Holmes, A.J., 2024. Functional brain networks are associated with both sex and gender in children. Science Advances, 10(28), p.eadn4202.
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., ... & Dale, A. M. (2018). The adolescent brain cognitive development (ABCD) study: imaging acquisition across 21 sites. Developmental cognitive neuroscience, 32, 43-54.
Rippon, G., Losse, K. and White, S., 2024. Impression management in sex and gender neuroscience research reporting: the MAGIC guidelines. Nature Communications, 15(1), p.2826.
Rippon, G., Jordan-Young, R., Kaiser, A. and Fine, C., 2014. Recommendations for sex/gender neuroimaging research: key principles and implications for research design, analysis, and interpretation. Frontiers in human neuroscience, 8, p.650.
Gruber, F.M., Distlberger, E., Scherndl, T., Ortner, T.M. and Pletzer, B., 2019. Psychometric properties of the multifaceted gender-related attributes survey (GERAS). European Journal of Psychological Assessment.
Stites, S.D., Cao, H., James, R., Harkins, K., Coykendall, C. and Flatt, J.D., 2023. A systematic review of measures of gender and biological sex: Exploring candidates for Alzheimer's disease and related dementias (AD/ADRD) research. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 15(1), p.e12359.
Rauch, J.M. and Eliot, L., 2022. Breaking the binary: gender versus sex analysis in human brain imaging. Neuroimage, 264, p.119732.
Nielsen, M. W., Stefanick, M. L., Peragine, D., Neilands, T. B., Ioannidis, J. P., Pilote, L., ... & Schiebinger, L. (2021). Gender-related variables for health research. Biology of Sex Differences, 12, 1-16.
National Institutes of Health Grants Notice, 2015. Consideration of Sex as a Biological Variable in NIH-funded Research, NOT-OD-15-102.
Fausto-Sterling, A., 2019. Gender/sex, sexual orientation, and identity are in the body: How did they get there?. The Journal of Sex Research, 56(4-5), pp.529-555; Joel, D.(2024). Nature v. Nurture, World Without Gender Substack.
Fine, C., Dupré, J. and Joel, D., 2017. Sex-linked behavior: evolution, stability, and variability. Trends in cognitive sciences, 21(9), pp.666-673.
Rippon, G., 2023. Mind the gender gap: The social neuroscience of belonging. Frontiers in Human Neuroscience, 17, p.1094830
Note that guest posts express the views of the author(s) and not necessarily the publishers and founders of A World Without Gender, which is expressly intended as a place where readers can encounter and explore different viewpoints on the topic.