Gender Equality in Appointments and Promotions: Two Proposals

The aim of this post is to put forward proposals to improve equality in academic appointments and promotions. The primary intention is to improve prospects for women academics, although these proposals would also benefit both women and men who have taken career breaks, work part time or who have worked in industry or other sectors. I propose two ideas that are detailed below: first, a move away from ‘career total’ publication metrics in favour of ‘personal best’ metrics; second, a commitment to gender balanced panels.

I am putting these proposals for discussion within the school/university in which I work. However, the problems (and solutions) are really quite general – certainly in the UK and probably internationally. Thus I am putting these ideas into the public domain because I would like to see them discussed and implemented across all institutions. I have also taken a ‘life science’ focus because that is the domain in which I work; I am sure that there are similar challenges in other fields.

Background

The graph shows a ‘typical approximate proportion’ of women and men at undergraduate, postgraduate, postdoctoral, assistant professor (lecturer), associate professor (senior lecturer / reader) and professorial level in a ‘typical’ Life Sciences department: these data are based on some real data but have been modified to give a straighter line and to preserve anonymity of the data sources.

women2

While the majority of students are female, the majority of staff are male, and the proportion of women decreases at every stage of career development. There are many complex reasons for this; nonetheless, this situation is a disgrace, not to mention a tremendous waste of talent. It is incumbent upon us to take action to remedy this. There are likely to be very many actions that could help. Here are two I propose: they are certainly not exhaustive.

Personal Best Metrics

My first proposed change is to stop using ‘career total’ publication metrics for appointments, promotions and academic biographies and move instead to ‘personal best’ metrics. Career total publication metrics include total number of papers authored, total citations, h-index and other such measures. For example, a university might have guidelines for the number of publications needed for a professorial appointment. These metrics discriminate against people who have had career breaks (especially women), worked in other (relevant) sectors (industry or public bodies) or who work part time (e.g. 80%; also often women).

The ‘personal best’ metrics I propose have solid precedent and foundation, namely in their use for REF. Here is an example of how such a system might work for appointment or promotion:

  1. The judgement is made on a suitable period prior to the appointment/promotion. For example, 6 years, as per the REF, seems very sensible.
  2. The applicants’ top 4 research outputs in this period are considered. These need to be outputs where the applicant is a leading author (i.e. first, last or corresponding author – note that this is tougher than a REF submission). The outputs also need to be ‘new’, i.e. not used for a previous appointment or promotion within the organization.
  3. Where somebody has worked part time, or has career breaks during the period, the number of outputs are reduced pro rata.
  4. The panel assigns star ratings to each of the outputs on a similar scale to the REF (i.e. 0-4, possibly with the option of using fractional values e.g. 2.5).
  5. For appointments, candidates can then be compared on the basis of their best outputs, with appropriate pro rata adjustments. This is a much fairer system than using career totals.
  6. For promotions, a set star rating is agreed which is then uniformly applied, with appropriate pro rata for part time staff. For example, for 11 starts for Associate Professor, 13 stars for full Professor etc.

These criteria would completely replace career total judgments. Other criteria (on teaching, contributions to the university, international reputation etc.) would of course remain in place. This would be a fairer, more transparent system because universities would be recruiting and promoting people on the basis of their best research. And this system would also be aligned with REF, which would itself have benefits. Moreover, I would suggest that we use these criteria when describing biographies of senior academics. We would not say “Professor X has published over 150 papers…” Instead, we would say “Professor X’s most important work has been Y, and most important recent work has been Z”. Thus we could also eliminate ‘career total’ as a mark of esteem and instead use a ‘personal best’ esteem narrative.

Fair Recruitment, Fellowship and Promotion Panels

The second change is to ensure that all panels for recruitment, fellowship and promotion decisions are mandated to be at least one third women (and, for that matter, at least one third men). This proposal is similar to Owen Barder’s Pledge. I have sat on all male panels, and was appointed to my current job by an all male panel. I am not suggesting that all male panels are necessarily intentionally biased, but it is very easy for unintended bias to become part of such a process. This proposal would apply to recruitment panels (for all staff – including post-docs as well as permanent academic staff), fellowship decision panels and promotion panels. A one third composition could be implemented as follows:

  1. Panels of size 3-5 must contain at least 1 woman (and at least 1 man).
  2. Panels of size 5-8 must contain at least 2 women (and at least 2 men).
  3. Panels of size 9-11 must contain at least 3 women (and at least 3 men).

These compositions would help to reduce unintended bias and, in my view, improve prospects for career progression for excellent women scientists.

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3 thoughts on “Gender Equality in Appointments and Promotions: Two Proposals

  1. Laudable though the intention behind this is, research into the gender gap in certain academic subjects (especially mathematically intensive ones) has shown pretty conclusively that it is not (nowadays) anything to do with bias in hiring practice. Nor, incidentally, is it due to innate sex differences in ability. It is absolutely clear now that the explanation is much more subtle and complex than that. See, for example, Ceci, S. J. et al. (2014), Women in Academic Science: A Changing Landscape. Psychological Science in the Public Interest, 15(3), 75-141. doi:10.1177/1529100614541236. I wish I could paste a hyperlink to this review article here, but there doesn’t seem to be any facility for it. It’s easy enough to find, though.

    Andrew Colman

    • Hi Andrew, thanks for the link, this is very interesting. It may well be that the situation is very different in the USA: the “data” I have used is from the Life Sciences and is not “Maths Intensive”. I agree though that the situation is extremely complex. Our newly established diversity committee (on which I have been placed) has suggested a wide range of possible factors/remedies. My suggestions are intended to be more radical.

      The maths departments I know fare far worse: for example, in Nottingham, there are so few women academic staff that it would be impossible to do any statistics or studies at all!

  2. I think this is entirely sensible *even without* the gender-discrimination question. We’re buried in mountains of trivial just-publish-something papers; why encourage more? And why waste time writing up equivocal, utterly dull results just for the sake of farting out a paper? The only virtue I can see in it is if they’re training papers for well-mentored grad students, and even then it should be understood that real papers ought to be more substantial. It’d also require more honest measures of expectable achievement: few will really hit it big more than once or twice in a career (and even that might come late, or very early), so what’s a respectable showing for your average academic scientist? Of course, you’d have to guard against gender discrimination there, too — in a department or discipline biased against women, the likelihood in a Letterman-like game of “something or nothing” that a paper will turn up as “nothing” when the lead author is a woman.

    Those very anxious to claim that no discrimination exists usually turn to Ceci and Hoff Summers, who function as the “there is no anthropogenic climate change” speakers in this conversation. There is considerable research by many others documenting pervasive gender discrimination, including recent studies showing hiring and salary bias and widespread sexual harassment and assault in biological-studies fieldwork.

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