Soylent Is People, and WEIRD Is White: Biological Anthropology, Whiteness, and the Limits of the WEIRD

Abstract

WEIRD populations, or those categorized as Western, educated, industrialized, rich, and democratic, are sampled in the majority of quantitative human subjects research. Although this oversampling is criticized in some corners of social science research, it is not always clear what we are critiquing. In this article, we make three interventions into the WEIRD concept and its common usage. First, we seek to better operationalize the terms within WEIRD to avoid erasing people with varying identities who also live within WEIRD contexts. Second, we name whiteness as the factor that most strongly unites WEIRD research and researchers yet typically goes unacknowledged. We show how reflexivity is a tool that can help social scientists better understand the effects of whiteness within the scientific enterprise. Third, we look at the positionality of biological anthropology, as not cultural anthropology and not psychology, and how that offers both promise and pitfalls to the study of human variation. We offer other perspectives on what constitutes worthy and rigorous biological anthropology research that does not always prioritize replicability and statistical power, but rather emphasizes the full spectrum of the human experience. From here, we offer several ways forward to produce more inclusive human subjects research, particularly around existing methodologies such as grounded theory, Indigenous methodologies, and participatory action research, and call on biological anthropology to contribute to our understanding of whiteness.

Is There a Sampling Bias in Research on Work-Related Technostress? A Systematic Review of Occupational Exposure to Technostress and the Role of Socioeconomic Position

“…Our review compared the socioeconomic distributions and analyses of SEP in research on work-related exposure to technostress to assess whether specific techno-stressors are distributed differently according to SEP. Our assessment shows that in a subsample of 13 studies, 11 studies collected data from workers with higher SEP compared to the general population, thus constituting a socioeconomic sampling bias. This socioeconomic sampling bias is, in part, an expression of the more general issue that behavioural studies routinely publish broad claims based on samples drawn entirely from Western, educated, industrialised, rich, and democratic (WEIRD) study populations [ 52 , 53 ]. Although samples in technostress studies show some variation with regard to geographic and political contexts, they have been focused on overly educated and rich populations and professions.…”

The Pandemic as a Portal: Reimagining Psychological Science as Truly Open and Inclusive

“…Specifically, we suggest that an intersectional analysis reveals a common origin of closed science and inequality in psychological science. In this vein, we posit that both closed science and inequity in U.S. psychology originated in a scientific culture created by wealthy White male scholars to cater to their own experiences, perspectives, and needs-a culture that overrepresents and over-values the experiences and perspectives of the relatively narrow set of people who created it (Clancy & Davis, 2019). Thus, it is not possible to separate a dimension of exclusion based on gender from one based on race, or family background, or disability, or language: These dimensions are fundamentally interlocking elements of a system that was set up to promote, value, and support one very specific set of people.…”

Biocultural approaches to transgender and gender diverse experience and health: Integrating biomarkers and advancing gender/sex research

“…However, we are aware of only a handful of studies that include MICBS. Moreover, outside of HIV-focused work, cross-cultural research on the health of TGD people remains scant as the majority of existing studies draw their samples from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) populations (Henrich, Heine, & Norenzayan, 2010;Clancy & Davis, 2019). Prior to 2016, most studies with physiological data inclusive of TGD people were conducted in clinical contexts, involved invasive sampling, and focused primarily on measuring the safety and efficacy of gender affirming hormonal therapies and/or surgeries (ie, medical transition) or HIV/AIDS.…”