Rethinking Standards and Reference Models

Standards and reference models are integral to science, health & medicine, and engineering; they are used in educating students, generating and testing hypotheses, designing products, and drafting legislation. Standards and reference models based on a single sex (or particular groups of men or women) can have damaging material consequences (see Case Study: Inclusive Crash Test Dummies). Standards and models are based on available data and are therefore sensitive to sampling decisions made in Study Designing Health & Biomedical Research and in Engineering Innovation Processes.

Science, medicine, and engineering often take the young, white, able-bodied 70kg male as the norm (see Figures 1 and 2). When studied at all, other segments of the population—women, gender-diverse people, the elderly, larger or smaller people, and non-white groups—are frequently considered as deviations from that norm. Occasionally women’s bodies set the norm, as in the example of osteoporosis diagnostic criteria (see Case Study: Osteoporosis Research in Men).

Standards and reference models are shaped by and shape gender norms:

  • 1. Standards often default to male. For example, in the 1970s the majority of automobile crash test dummies modeled only the 50th percentile U.S. man. A wider range of dummies—representing diverse heights and weights—are now available for vehicle safety tests, but these are still based on male anatomy and leave out many, such as the elderly or people classified as obese (see Case Study: Inclusive Crash Test Dummies).
  • 2. Gender norms influence the choice of reference species. For example, primatologist Linda Fedigan has discussed the 1950s myth of the “killer ape," the pervasive image of primates engaged in bullying aggression toward females and violent infighting among males. This image of aggressive primates was drawn almost exclusively from studies of savannah baboons—taken as a “reference species”—in a process that Fedigan has called the "baboonization" of primate life (Fedigan, 1986).
  • 3. Reference subjects influence gender norms. For example, in rodent research, “reference females” are usually non-pregnant and non-lactating. Behaviorally, these females are less aggressive than males—a finding congruent with assumptions about gender. Changing the female mouse model to a pregnant or lactating animal would alter the outcome of a behavioral study: female mice are aggressive in controlling food sources when pregnant or caring for pups (Brown et al., 2010).
  • 4. Standards often assume a sex binary. By integrating large amounts of omics systems biology researchers hope to develop tools that integrate biological and cultural factors. Models in systems biology are currently biased toward a cis-male default. As researchers diversify their data collection to build more inclusive models, they should consider cis-women and gender-diverse individuals, as well as a range of intersecting factors like age and sociocultural background (see Systems Biology).

Significant gendered innovations result when researchers and engineers critically analyze standards and reference models for sex and gender bias, and revise as necessary by asking:

  • How are standards established? What input do stakeholders have, and who is identified as a stakeholder? What are the goals of specific standards, and how is progress toward these objectives assessed? Will the outcomes of research be applied or offered to groups not represented by the standard, such as individuals of a different sex?
  • How are models chosen? What reference models are preferred in a given discipline, and how and why were they selected? Would adopting a different reference model produce a different outcome or lead to different conclusions about sex and gender?


When analyzing human standards and reference models, researchers/engineers will want to consider the following questions:

  • a) Does the existing model differentiate between women, men, and gender-diverse people?
  • b) Are existing standards up-to-date, or based on old data that might be invalidated by trends? For example, the incidence of obesity has increased significantly in highly developed countries over time (WHO, 2011). Japan, Brazil, the U.K., and the U.S. have all seen rates of obesity roughly triple in less than 30 years (Jeffrey et al., 2008). Crash test dummies based on old norms may not represent most people (see Case Study: Inclusive Crash Test Dummies).
  • c) If a model does not consider sex, is it based on research in both sexes, or is it in fact a male reference model (or, in some cases, a female reference model) that is being improperly used as a generic “human” model?
  • d) If standards do consider sex, how important is sex to the reference model? Have researchers adequately investigated non-biological influences due to gender and other social or biological factors? Have researchers considered gender-diverse people and people undergoing gender-affirming medical therapies?
  • e) Beyond considering sex differences, does the model address sex-specific factors among women (such as pregnancy), men (such as susceptibility to prostate cancer), and gender-diverse people (such as hormone therapy)?
  • f) Does the existing model take into account differences between women’s, men’s, and gender-diverse people's attitudes, needs, and interests?
  • Are reference models based on male animals being used as reference models for the species overall?

When analyzing experimental reference models, researchers will want to consider the following questions:

  • a) Are reference models by default based on one sex but taken to be valid for the species overall?
  • b) Do data for one sex lag behind data for another sex, so that sex-specific reference models may not be equally developed or validated? Have researchers tried to collect data from gender-diverse people?
  • c) What criteria are used in selecting species, strain, and sex of model organisms used in research that will be translated to humans?
  • d) Does the choice of a particular model organism significantly affect findings?

Works Cited

Brown, R. S. E., A. E. Herbison, and D. R. Grattan. 2011. Differential Changes in Responses of Hypothalamic and Brainstem Neuronal Populations to Prolactin during Lactation in the Mouse. Biology of Reproduction 84 (4): 826-836.

Fedigan, L. (1986). The Changing Role of Women in Models of Human Evolution. Annual Review of Anthropology, 15, 25-66.

Hosey, L. (2001). Hidden Lines: Gender, Race, and the Body in Graphic Standards. Journal of Architectural Education, 55 (2), 101-112.

Jeffrey, R., & Sherwood, N. (2008). Is the Obesity Epidemic Exaggerated? No. British Medical Journal, 336 (7638), 245.

Le Corbusier (Jeanneret, C.). (1954). The Modulor: A Harmonious Measure to the Human Scale Universally Applicable to Architecture and Mechanics. Cambridge: Harvard University Press.

Sandring, S. (Ed.) (2004). Gray’s Anatomy: The Anatomical Basis of Clinical Practice, 39th Edition. Philadelphia: Churchill-Livingstone.

World Health Organization (WHO). (2011). Global Database on Body Mass Index (BMI): Percentage of Obese Adults (BMI ≥ 30) by Country and Year.



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