Blogpost 5: Gender disparities in research funding, bias and equality policies: the need for new evidence

Gender disparities in research funding, bias and equality policies: the need for new evidence

By Laura Cruz-Castro and Luis Sanz-Men├ęndez (CSIC Institute of Public Goods and Policies)

Posted on June 29th 2021

In general, women scientists apply less for research funding, get less funds for research, and have lower success rates compared to applicants than men (Cruz-Castro and Sanz-Men├ęndez 2020). These have been general claims in the academic literature and the policy discourse, although recent evidence indicates that in some highly competitive funding agencies like the ERC in Europe or the NIH and NFS in the US, this is no longer the case. (Cruz-Castro, Ginther and Sanz-Men├ęndez 2021).

The relation between gender disparities and potential evaluation bias is a main focus of the GRANteD project. Conceptual confusion often leads to imprecise causal arguments. For example, it is possible that all bias produces inequality, but not all inequality or difference is the result of bias. It is important to point out the existence of conceptual differences between results and processes (Cole and Fiorentine 1991). In order to explain gender differences in the results of the allocation of competitive funding, it is necessary to construct plausible explanatory theories, appropriate evidence and counterfactuals, and to acknowledge the limits of observational evidence to demonstrate the existence of processes, in the context of the peer review evaluation, that determine these different results (van den Besselaar et al. 2020).

In relation to the differences between men and women in competitive research funding, emphasis has been placed in two themes: application and success. Women, in relation to the pool of potential applicants, apply less, both in individual applications and in the role of PI of teams (NAS 2007). Additionally, women seem to have slightly lower rates of success compared to men, although some recent evidence indicates that differences are no longer significant and that, in some scientific domains and countries, they operate in the opposite direction (European Commission 2019).

With the aims of promoting female participation and increasing success rates of women, gender equality policies in science have been increasingly developed across Europe for more than 20 years. The diagnoses, in general, may have suffered from the aforementioned confusion between processes and results, and, in some cases, put the emphasis on discriminatory practices as the main causes of the differences (e.g. stereotypes, unequal treatment, biased evaluations against women, etc.). But beyond the quality of the diagnosis of those interventions, it is fair to acknowledge that equality policies have put the issue on the agenda, that they have called for diversity in science, and that they have put in place important initiatives; for example, extending the maternity eligibility periods, insisting on the vigilance of language, or the need to avoid the activation of stereotypes (European Commission 2009) – all initiatives that seem to be associated with the closing of the gaps. However, some issues, like the establishment of gender quotas, have been subject to debate (Vernos 2013) and may rise concerns about intended consequences related to reverse discrimination.

In addition, equal success rates for men and women do not guarantee that the assessment and allocation process has not been discriminatory or biased. If that was the case, gender bias would be easily solved by public policies and funding agencies: they would only have to define a baseline, for example, the proportion of applicants by gender, and distribute the available funding proportionally. Would this be acceptable? Would it be for politics? For funders? For the scientific community? The idea is at least controversial.

The implementation of gender equality policies in the research arena, especially at the research funding organizations level, has not always been based on the appropriate diagnosis and the availability of evidence. It could be said that, in general, they have been based on limited evidence, almost all observational and based on associations and correlations, without sound theories and counterfactuals. On the other hand, on the academic side, the evidence from the scientific literature is not conclusive either (Ceci et al. 2014), neither on the existence of significant funding differences (once performance factors are taken into account), nor about the causes (e.g. bias), especially when other intervening factors are considered.

An additional problem to the methodological shortcomings of the literature is that research funding is context specific. Policies that have been successfully implemented in one place cannot be transferred to another environment, assuming that if they worked somewhere, they will work anywhere; this is a general problem of policy imitation that is worsened if it is combined with the lack of proper evidence (Cartwright and Hardie 2012).

The original design of the GRANteD project intended to provide robust empirical evidence to diagnose the causes of differences in results (application, grants and effects on careers), and to address the analysis of the (intended and unintended) effects of gender equality policies in funding agencies; this requires the collaboration of the funding entities, and their willingness to discover successes and possible pitfalls.

Many agencies have created gender equality units, which have developed their own objectives, equality plans, and proposed modifications to the procedures. In some of them, the issue has become central on the agenda and gained visibility. But the promotion of equality may be in tension with equity and fairness (communalism as part of the scientific ethos). For the sake of legitimacy, the agencies will gain by providing evidence that the implementation of gender equality policies does not come at the cost of fairness and quality of the funding outcomes.

Funding agencies are faced with finding a balance between two principles or two institutional logics: the logic of equality and the logic of equity (fairness). Equity here corresponds to the logic of merit, as opposed to the logic of equality, which responds to normative principles and values of our societies which make them more diverse and inclusive. The promotion of equality between men and women should be done much more on the basis of the correct diagnosis of the causes of the differences, and less on the basis of imitation, or on the basis of the social recognition that can be obtained, in the short term, from this strategy; social desirability bias should be avoided in this type of policy intervention.

Having an adequate diagnosis of the causes of the differences is vital for the research evaluation system and for the quality of the policy proposals. Knowing if there are problems derived from previous segmentation, the presence of stereotypes, diverse preferences (including those related to attitudes towards competition or to the balance between work and personal life (Kahn & Ginther 2018), is key for understanding whether policies and interventions have had any causal effect. Here, GRANteD should provide new theoretically-grounded empirical evidence on the causes of the differences, before concluding on the appropriateness or effectiveness of gender equality policies and practices in research funding agencies. A value added of the project could be to demonstrate the effects (and causal connections) of the implemented policies on the outcomes.

Interventions on competitive research funding instruments and agencies are not the only, and perhaps not the better locus of action for gender equality policies (Steward and Valian 2018). In order to address some of the most important causal factors of the gender differences in research funding, the targets should include schools, universities, research centers, firms and teams. A shift in attention is needed.

 

References

Cartwright, N., & Hardie, J. (2012). Evidence-Based Policy: A Practical Guide to Doing It Better. Oxford University Press.

Ceci, S. J., Ginther, D. K., Kahn, S., & Williams, W. M. (2014). Women in academic science: A changing landscape. Psychological Science in the Public Interest. 15(3) 75-141.

Cole, S., & Fiorentine, R. (1991). Discrimination against women in science: The confusion of outcome with process. In H. Zuckerman, J. R. Cole, & J. T. Bruer (Eds.), The Outer Circle: Women in the Scientific Community (pp. 205ÔÇô226). Yale University Press.

Cruz Castro, L., & Sanz Men├ęndez, L. (2020). Grant Allocation Disparities from a Gender Perspective: Literature Review. Synthesis Report. https://doi.org/10.20350/digitalCSIC/10548

Cruz-Castro, L., Ginther, D.K. & Sanz-Men├ęndez, L. (2021). Gender and Underrepresented minorities differences in research funding. Paper presented at EU-SPRI 2021, 9-11 June 2021, Oslo (track 10)

European Commission (Ed.). (2009). The gender challenge in research funding: Assessing the European national scenes. Office for Official Publ. of the European Communities.

European Union. (2019). She figures 2018. Publications Office of the European Union.

Kahn, S., & Ginther, D. (2018). Women and Science, Technology, Engineering, and Mathematics (STEM): Are Differences in Education and Careers Due to Stereotypes, Interests, or Family? In S. L. Averett & L. M. Argys (Eds.), The Oxford Handbook of Women and the Economy. Oxford University Press.

National Academy of Sciences, National Academy of Engineering, & Institute of Medicine. (2007). Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering. National Academy of Sciences.

Stewart, A. J., & Valian, V. (2018). An Inclusive Academy. Achieving diversity and excellence. The MIT Press.

Van den Besselaar, P., Mom, Ch., Cruz-Castro, L., Sanz-Menendez, L. Hornbostel, S., Moller, T., Sandstrom, U., Schiffbaenker, H., Holzinger, F. and Husu, L. (2020). Identifying gender bias and it causes and effects. GRANteD D2.1. https://www.granted-project.eu/wp-content/uploads/2021/04/GRANteD_D2.1.pdf

Vernos, I. (2013). Quotas are questionable. Nature, 495, 39.