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• A reply to Solle, Streed and Restar
  John Armstrong, Alice L Sullivan and George M Perry
  Published on: 26 January 2024
• Appropriate and robust methods needed when assessing athletic performance of non-binary athletes
  J Solle, Carl G Streed Jr and Arjee Restar
  Published on: 16 January 2024

• Published on: 26 January 2024

  A reply to Solle, Streed and Restar

  • John Armstrong, Reader in Financial Mathematics King's College London
  • Other Contributors:
    • Alice L Sullivan, Professor of Sociology
    • George M Perry, Independent Researcher

  Solle et al. argue that our study “supports a conclusion for the relationship between sex and race time, as a result of the poorly constructed and likely miscategorized sex variable”. However, if this view were correct, some other explanation would be needed to explain the statistically significant correlations we found between sex and race time. Solle et al. do not provide any such explanation.

  They state that our methodology is “unreliable”. But we do not assume that our model for sex is perfectly reliable, and we emphasize throughout that we model sex probabilistically. As we explain in the appendix to our paper, and illustrate with a numerical example, if one increases the uncertainty in our model this would indicate that there is an even stronger relationship between sex and race times. Solle et al. do not consider this point in their response, and as a result they fail to explain how their theory can be reconciled with the data.

  In the absence of such an argument, we believe that their theory cannot be reconciled with the data and so must be in some way flawed. We believe that the flaw in their argument is to overstate the difficulty in ascribing a sex to a non-binary athlete. For example, Solle et al. give the impression that we modelled non-binary athletes’ sex using only their names, yet for the majority of non-binary athletes we could determine their sex from their race history.

  Solle et al. go on to argue that our use of the terminology “na...

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  Solle et al. argue that our study “supports a conclusion for the relationship between sex and race time, as a result of the poorly constructed and likely miscategorized sex variable”. However, if this view were correct, some other explanation would be needed to explain the statistically significant correlations we found between sex and race time. Solle et al. do not provide any such explanation.

  They state that our methodology is “unreliable”. But we do not assume that our model for sex is perfectly reliable, and we emphasize throughout that we model sex probabilistically. As we explain in the appendix to our paper, and illustrate with a numerical example, if one increases the uncertainty in our model this would indicate that there is an even stronger relationship between sex and race times. Solle et al. do not consider this point in their response, and as a result they fail to explain how their theory can be reconciled with the data.

  In the absence of such an argument, we believe that their theory cannot be reconciled with the data and so must be in some way flawed. We believe that the flaw in their argument is to overstate the difficulty in ascribing a sex to a non-binary athlete. For example, Solle et al. give the impression that we modelled non-binary athletes’ sex using only their names, yet for the majority of non-binary athletes we could determine their sex from their race history.

  Solle et al. go on to argue that our use of the terminology “natal sex” is “pathologizing and stigmatizing”. This could be seen as ruling out the use of a gender-critical operationalization of sex in our analysis irrespective of the data. However, to determine the effectiveness of a scientific model, one should be guided by empirical evidence. Solle et al.’s argument would appear to be ideological rather than scientific.

  Solle et al. also state that our findings “should not have any implication in law or policy”. However, in the UK, the Equality Act 2010 it is unlawful for service providers to indirectly discriminate on the basis of sex. Our results therefore suggest that, as males would be more likely to win than females, a single non-binary race category is likely to be unlawful.

  References

  1. New York Road Runners. RBC Brooklyn Half. 2022; Available from: https://www.nyrr.org/races/2022/rbcbrooklynhalf.
  2. New York Road Runners. 2022 RBC Brooklyn Half Race Results. 2022; Available from: https://results.nyrr.org/event/22BKH/result/4989?_gl=1*1t0wrhz*_gcl_au*M....

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  Conflict of Interest:
  None declared.

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• Published on: 16 January 2024

  Appropriate and robust methods needed when assessing athletic performance of non-binary athletes

  • J Solle, Pride Run Director Front Runners New York
  • Other Contributors:
    • Carl G Streed Jr, Clinician-Investigator
    • Arjee Restar, Assistant Professor

  Inclusion for non-binary athletes in racing events has progressed in the last three years, with five of the six Abbott Major Marathons offering non-binary running categories in 2023. Given that the “main issue for non-binary people is that they cannot compete authentically” without the non-binary category1, non-binary race divisions were created, in part, as inclusion measures for non-binary individuals. As the number of non-binary athletes participating in running is increasing2, the representation and needs of non-binary athletes should be studied using appropriate methods that are in line with current best practices3, particularly in assessing gender and sex measurement and analyses. In their paper, “Performance of non-binary athletes in mass-participation running events,” Armstrong et al. utilize several methodological approaches and analyses that do not appropriately assess the performance of non-binary athletes. As a consequence, the conclusions of the paper introduce numerous biases with results that do not accurately reflect the reality of non-binary athletes.

  In designing their study, the authors attempt to determine the sex assigned at birth (labeled natal sex in their model) of non-binary athletes based on the presumed sex assigned at birth of their names. This approach is methodologically unreliable and flawed4. Specifically, the authors fail to distinguish between sex assigned at birth, legal sex, and any sex-related medical intervention that the athle...

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  Inclusion for non-binary athletes in racing events has progressed in the last three years, with five of the six Abbott Major Marathons offering non-binary running categories in 2023. Given that the “main issue for non-binary people is that they cannot compete authentically” without the non-binary category1, non-binary race divisions were created, in part, as inclusion measures for non-binary individuals. As the number of non-binary athletes participating in running is increasing2, the representation and needs of non-binary athletes should be studied using appropriate methods that are in line with current best practices3, particularly in assessing gender and sex measurement and analyses. In their paper, “Performance of non-binary athletes in mass-participation running events,” Armstrong et al. utilize several methodological approaches and analyses that do not appropriately assess the performance of non-binary athletes. As a consequence, the conclusions of the paper introduce numerous biases with results that do not accurately reflect the reality of non-binary athletes.

  In designing their study, the authors attempt to determine the sex assigned at birth (labeled natal sex in their model) of non-binary athletes based on the presumed sex assigned at birth of their names. This approach is methodologically unreliable and flawed4. Specifically, the authors fail to distinguish between sex assigned at birth, legal sex, and any sex-related medical intervention that the athletes may have had, conflating them. This technique is not novel, but rather a misapplication of methods. As a result, the authors are analyzing assumed sex assigned at birth and race times, but assume that it accounts for gender. The model does not analyze gender. As a member of an organization whose athletes are a part of this analysis, we can confirm that errors are present.

  Principles of research methods dictate that the design of a study must align with the study's objectives and the context of the phenomenon. However, in Amstrong’s case, the authors’ particular use of language describing natal sex shows their use of a pathologizing and stigmatizing framework in viewing the phenomenon, which is misaligned with current best practices in trans health research5. Confirmation bias is present in the way the authors attempt to guess sex assigned at birth and design the independent variable labels. Treating gender identity as “natal-female nonbinary” or “natal-male nonbinary” is still miscategorizing non-binary athletes. Finally, the authors introduce non-neutrality bias as they favor sex assigned at birth as a concept over gender identity by saying “sex has considerable explanatory advantages over gender identity” without providing evidence to support this.

  These poorly chosen methods, apparent biases, and lack of reasonable evidence lead to inaccurate conclusions. The authors state that "...if one wishes to understand the needs of gender non-conforming individuals, it is vital to control for sex as it is likely to play a significant role in any analysis." Because the analysis only supports a conclusion for the relationship between sex and race time, as a result of the poorly constructed and likely miscategorized sex variable, we know nothing about the needs of gender non-confirming individuals at all.

  The methods of this paper are misapplied and not robust. Importantly, the non-binary category in running helps to validate the identities of non-binary individuals1. The author's conclusion that sex and gender data should both be collected does not disprove any concepts regarding the importance of gender identity and relating to social determinants is an inappropriate conclusion. As a result of these misapplications, the findings cannot and should not have any implication in law or policy. Future research to better understand the needs of this population should include non-binary runners themselves, as non-binary runners are likely experts in their own needs6,7.

  References

  1. Erikainen, S., Vincent, B., & Hopkins, A.. Specific Detriment: Barriers and Opportunities for Non-Binary Inclusive Sports in Scotland. Journal of Sport and Social Issues, 2022; 46(1), 75-102.

  2. Bernhard, J. What Does It Take to Design an Inclusive Running Race? - Uncommon Path – An REI Co-op Publication. REI. 2023. https://www.rei.com/blog/run/inclusion-in-running (accessed 11 January, 2024)

  3. Reisner SL, Deutsch MB, Bhasin S, et al. Advancing methods for US transgender health research. Curr Opin Endocrinol Diabetes Obes. 2016 Apr;23(2):198-207.

  4. Blevins, C., & Mullen, L. DHQ: Digital Humanities Quarterly: Jane, John … Leslie? A Historical Method for Algorithmic Gender Prediction. Alliance of Digital Humanities Organizations. 2015

  5. Ruane, J. M. Essentials of research methods: A guide to social science research. Malden, MA: Blackwell Publishing. 2005

  6. Solle JC, Steinberg A, Marathe P, Gray TF, Emmert A, Abel GA. Patients as experts: characterizing the most relevant patient-reported outcomes after hematopoietic cell transplantation. Bone Marrow Transplant. 2020 Jan;55(1):242-244.

  7. Streed CG Jr, Perlson JE, Abrams MP, Lett E. On, With, By-Advancing Transgender Health Research and Clinical Practice. Health Equity. 2023 Mar 3;7(1):161-165.

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  Conflict of Interest:
  None declared.

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