Comment on the Proposal to Rename the R.A. Fisher Lecture

See the attached PDF file.

I agree with the suggestion of Crane, Guinness and Martin to retain the name of the Fisher Lecture. We have to see/value (objective) ideas and contributions to science and society that are timeless, separately from personal statements, beliefs,... that don't align with (subjective) norms and values in a different zeitgeist.

A detailed critique of Crane, Guinness, and Martin's Statement has been posted on Twitter by Maryclare Griffin (Griffin, June 13 2020) and I refer to it here so that readers can easily access it. A recent tweet by Crane characterized the social media discussion as "[a] lot of emotional appeals and shaming, which only silences those who think differently" (Crane, June 14 2020). I encourage the authors to grapple with and respond to the well-researched arguments that Griffin and others have articulated on social media. More generally, the present Statement lacks both proper attribution and a serious engagement with the perspectives that it argues against. I am disappointed to find that the Statement does not meet the intellectual standards to which its authors otherwise hold themselves and others, and I look forward to a revision.

At the risk of rehashing the above-referenced arguments but more ineffectively, I will emphasize a few of my own thoughts with respect to this Comment:

- The Proposal is to rename the Fisher Lectureship, not to erase Fisher's contributions to statistics or to erase his name from those contributions: the proposal does not seek to retract Fisher's scholarly works or to rename the Fisher information, F-distribution, Fisher-Tippet-Gnedenko theorem, etc. Statisticians should continue to teach and indeed celebrate these contributions. Statisticians should also teach about the role that eugenics played in Fisher's intellectual life, in part to illustrate that practice of statistical science is not objective or neutral, and that valuable methodological contributions do not alone entail good science.

- Crane, Guinness, and Martin seek to judge Fisher's contributions to statistics "independently of the individual with whom those ideas originated". To the extent that this is possible (see next point), this goal still appears consistent with removing Fisher's name from the award.

- However, there is existing research that problematizes the idea that Fisher's contributions to statistics can be separated from his work in eugenics (references provided in Griffin (June 13 2020); see also e.g. Mazumdar (1992), Louçã (2009), and references therein).

Finally, while not stated explicitly by Crane, Guinness, and Martin in this Comment, a core concern appears to be that we ourselves may be judged equally harshly in the future (Crane, June 10 2020). I hope we are; we are not owed an award named in our honor and nor is Fisher.

References:

Harry D. Crane (June 10, 2020, 8:07 a.m.) https://mobile.twitter.com/HarryDCrane/status/1270704215271321601

Harry D. Crane (June 14, 2020, 12:38 p.m.) https://mobile.twitter.com/HarryDCrane/status/1272221926988095491

Maryclare Griffin (June 13, 2020, 6:01 p.m.) https://mobile.twitter.com/mcmcgriffin/status/1271940745193275393

Louçã, F. (2009). Emancipation Through Interaction–How Eugenics and Statistics Converged and Diverged. Journal of the History of Biology, 42(4), 649-684.

Mazumdar, P. (2005). Eugenics, human genetics and human failings: the Eugenics Society, its sources and its critics in Britain. Routledge.

Plenty of people make great contributions to many fields--and yet we do not honor them. He did more than support eugenics or have problematic "views." He supported and advocated for social systems that oppressed and killed others, including defenses for actual Nazis. One can respect a person's accomplishments without naming a lecture after them. Why support a man who actively fought against efforts to denounce racism? Why venerate this person with a distinguished lectureship? There is simply no need to do it. If you want to honor the accomplishment, perhaps name it in honor of a statistical term or in honor of a kind of model or discovery.