Gender and Housework

There is an article on getting help with housework on the Science Careers website. It is based on an article in the magazine of the American Association of University Professors, Academe, Housework is an Academic Issue, by Londa Schiebinger and Shannon K. Gilmartin. Schiebinger and Gilmartin's article is based on research on dual career couples in academia, Dual-Career Academic Couples: What Universities Need to Know. They analysed survey results from 910 men and 312 women with partners of the other sex. (There were not enough same-sex partners for quantitative analysis.) Among other things they found that there are no significant differences between male and female academic scientists in the number of paid hours worked (see Figure 4 of their article) but considerable differences between male and female scientists in the amount of time spent on household tasks: female scientists do twice as much housework as their male counterparts.. They also found that the task most likely to be outsourced is cleaning and the group most likely to outsource cleaning are women scientists with an academic partner. For both men and women outsourcing housework is associated with higher productivity. Schiebinger and Gilmartin suggest as a policy recommendation that institutions consider offering 'cafeteria' or 'flexistyle' benefits packages from which employees could choose benefits up to a specified amount, for example, some might choose assistance with housework, others help with child care and others help with elder care.

The Science Careers article focussed on hiring help with childcare and housework. It includes an interview with a female professor at MIT whose husband is a professor at Harvard who have a nanny, a cleaner and someone who comes in to cook twice a week as well as being able to leave the children with their grandparents if they need to be away for conferences. As an illustration of a possible solution to coping with the demands of an academic job it is excellent. However, Isisthescientist, in a post about the hoary old question of whether men and women differ in their aptitude for science and maths, mentioned the reaction of another women scientist blogger to the Science Careers article. Essentially this was that the article appeared to take for granted that women need advice on coping with housework but men do not. The editor of Science Careers, Jim Austin, responded to these remarks on the Science Careers blog leading to further discussion at Isisthescientist. I think we need to appreciate that women are not a homogenous group. Some women will have found the article helpful: others may feel that it reinforces stereotypes rather than challenging them. The head of department who advises new female assistant professors to get over people's expectations of what women should do around the house and get paid help with housework is still better than one who does not recognise the issue at all, even if the advice could equally apply to new male assistant professors. Likewise a head of department who tells female lecturers going on maternity leave about the university's flexible working policies but not male lecturers going on paternity leave is still better than one who gives the impression that anyone who works part time is lacking commitment. We should celebrate progress, even if it is tiny incremental steps.

A related post from a different blog is How did we get here?, in which a male doctor ponders how it came about that, by default, he became the primary earner while his wife stays at home. Comment 4 is particularly interesting.

I wonder if the asymmetry between maternity leave entitlement and paternity leave entitlement is a factor in women becoming the default stay at home partner? Note I am not saying the only factor. Of course factors like husband earns more, husband is at a crucial stage of career and you would quite like to have at least one income, the difficulty of finding flexible work and cultural and family expectations are important. I just wonder whether patterns who does what become established while the mother is on maternity leave and then become difficult to break when she goes back to work.

Over the years I have met quite a few women whose careers have been compromised or effectively ended by their decision to spend time with their children. I cannot recall one of them saying that they wished they had spent less time with their children. I have met men who wished they had spent more time with their children. If we want real equality then we have to acknowledge that parents want to spend time with their children, regardless of whether they are the father or the mother. Men are people too.

Academic Promotions

Suppose a university, or one of its components, for example a school, faculty or department, collects data on promotions and discovers that the rate at which women are promoted is statistically indistinguishable from the rate at which men are promoted. What could this mean?

Possibilities include:

1. There is no difference between men's and women's experience of the promotion process.
2. There is a difference but it is too small to resolve with the data available. (Attempts to aggregate data from different years need to take into account that the outcomes in year N are not independent of the outcomes in years N-1, N-2,... .)
3. There is a difference but it does not manifest itself in differences in promotion rates but in some other way, for example, increased stress.
4. Men and women tend to have different expectations of a promotion procedure. For example, it may be the case that women tend to believe that if they meet the criteria then they will be promoted while men tend to believe that if they are better than the other guy then they will be promoted.
5. Men and women find the promotions procedure equally unfair but women interpret their experience within a paradigm of women's disadvantage while men use a different paradigm, for example, managerial incompetence.

Well constructed staff surveys would help distinguish among these possibilities.

A particularly interesting situation occurs when it is widely accepted that women are less likely to be promoted than men, even though the evidence that this is the case is statistically unconvincing. Not only may it be accepted that women are less likely to be promoted but it may also be accepted that the reason is that women are less likely to apply for promotion, even though the evidence that this is the case is also unconvincing. In fact people may be so strongly convinced that women are less likely to apply for promotion that they propose research projects to investigate why this is the case. To a scientist this is an interesting concept: a proposal to investigate the reasons for an effect that you can't demonstrate actually exists.

When there is a widespread perception that women are disadvantaged by the promotions procedure then it is necessary to be seen to be addressing the problem, even if the data do not support its existence. In this case the 'women are less likely to apply' explanation has a political advantage. It throws the responsibility for the perceived situation onto the women involved which means that proposed remedies can focus on modifying the behaviour of the women rather than on altering the procedures or the way they are implemented. It is generally easier to persuade people of the case for modifying someone else's behaviour rather than their own. Why is this an advantage? Well, it is if it means something happens rather than nothing. Of course there are women who find the 'here is our special help for the ladies' approach offensive but in my experience they are out-numbered by those who will take whatever assistance is offered regardless of the motives of those who are offering it.

The Quota Question

Are quotas useful? The answer to this question depends on what you are trying to achieve. If the problem is defined by the statement ‘there are too few women at a particular level or in a particular occupation’ then imposing sanctions, or threatening to impose sanctions, on those who fail to meet a quota will increase the number of women, provided there are a sufficient number of suitable qualified women to fill these positions.

In Norway companies were given six years to raise the percentage of women on boards to 40%. Some think that the Norwegian experience shows that the talent was there. It was simply a matter of identifying it. (‘Quotas for women on the board: do they work?’, The Sunday Times 8 June 2008, see also this comment at 20-First. However, a study by Amy Dittmar and Kenneth Ahern of the Ross School of Business at the University of Michigan showed that the performance of firms dropped as the percentage of women on the board increased. The study found that this was due to a shortage of appropriately qualified women so that boards had to appoint inexperienced women in order to meet their quota. (See also ‘Just Don’t Call Them Gender Targets: The Need to Move Diversity Hiring into the Open’ at www.theglasshammer.com. Thanks to Suzanne Doyle-Morris for alerting me to this post via LinkedIn.)

Another area where quotas operate is in the electoral process, for example, nine European countries have legislated candidate quotas and twenty-two have voluntary political party quotas (source: www.quotaproject.org). In an ideal world we would not have interventions such as all women candidate lists, but we do not live in an ideal world. A representative democracy is entitled to take steps to ensure that it actually is representative. What about the ‘best person for the job’ argument? There is evidence that voters use heuristics such as appearance to judge the competence of candidates and that this can lead to gender bias. There is also some evidence people rely less on gender stereotypes when they are familiar with female politicians. [‘Inferences of Competence from Faces Predict Election Outcomes’, Todorov et al. Science 10 June 2005:Vol. 308. no. 5728, pp. 1623 – 1626; ‘A neural basis for the effect of candidate appearance on election outcomes’, Spezio et al. Soc Cogn Affect Neurosci 3, 344-352; Chiao JY, Bowman NE, Gill H (2008); ‘The Political Gender Gap: Gender Bias in Facial Inferences that Predict Voting Behavior’, PLoS ONE 3(10): e3666. doi:10.1371/journal.pone.0003666; ‘Powerful Women: Does Exposure Reduce Bias?’, Beaman et al. MIT Department of Economics Working Paper No. 08-14 1 August 2008.] It seems reasonable to have some sort of intervention to accelerate progress.

Could quotas work in academia? Currently quotas are illegal in the UK under the Sex Discrimination Act (1975), since the existence of a quota implies that women would be appointed in order to meet the quota. If quotas were legal how would they operate? Would the quotas apply to staff employed or to new appointments? If the former the quotas would have to take into account the current levels of women in universities as otherwise institutions could be penalized for actions that occurred before the quotas were set, which seems unfair. If the latter, what would be the effect? Suppose turnover is 5% per year (since a career as a permanent academic lasts about thirty years, we would expect about 3% per year but there will also be contributions due to transfers between institutions and expansion). If half of new appointees are women then, assuming no women leave via retirement or transfer, the percentage of women among academics would rise at 2.5 percentage points per year, which may not sound much but a department that achieved this could get from 25% women to 50% women in ten years. Would the quotas apply to institutions as a whole, with institutions developing their own plans to meet them, which might encourage them to focus on subjects where recruiting women was easier, or on a subject by subject basis? The former seems unlikely given that 48% of lecturers in Higher Education in the UK in 2007-08 were female (HESA press release). If the quotas are set on a subject by subject basis, what form would they take – five out of ten appointments, ten out of twenty? How would the quotas be enforced? What penalties would there be for failing to comply?

What would the advantages be? Clearly, quotas could be effective over a timescale of ten years or so. What would the disadvantages be? Many women would be opposed because they want to be appointed for their ability not their sex. Many men would feel unfairly treated. Some women already find that any recognition they receive is belittled on the grounds that they were recognised for their gender not their achievements because men believe, despite the evidence, that women are unfairly advantaged. Quotas are a top-down measure, which is culturally inappropriate for universities. Many academics would devote their energies to finding ways around them.

So, quotas would be effective if the primary concern is simply to increase the numbers of women. However, there are a number of significant drawbacks.

Personally, though quotas may be useful in other areas, I am opposed to quotas in academia. I would want to be offered a job because the selection panel believed I was the best fit to the requirements of the position, not because they need a woman to meet a quota. Likewise, I think that being short-listed for interview so that some administrator can tick the ‘woman interviewed’ box is a waste of my time, and of the selection panel’s. I think there are better, less divisive ways of achieving increases in the number of women in permanent academic posts, such as the STRIDE project at the University of Michigan.

Over-Interpreted Data 3

This example of data that does not support the inferences drawn from it is quite subtle. In the Campaign for Science and Engineering in the UK Policy Document Number 8, May 2008, ‘Delivering Diversity: Making Science & Engineering Accessible to All’ is the graph shown in Figure 1. It is noted that more women entered the system as researchers and were promoted at every subsequent level. However, the comment is also made that, while in an equal world the graph would be flat so that the percentage of women at higher levels matched that at lower levels, there is no sign of the rate of increasing under-representation abating, i.e. the slope in 2005/06 is pretty much the same as the slope in 1995/96. But the graph shows that the percentage of women at each level in 2005/06 matches that of the next lowest level ten years previously, which is roughly what you would expect as each cohort moves through the system. Since the percentage of women among researchers rose for the slope to flatten the percentage of women among professors, senior lecturers and lecturers would have to have risen faster. This raises the question: is the fall-off in the percentage of women with grade the result of current discrimination or disadvantage preventing women from moving through the system from researcher to professor or is it the result of discrimination or disadvantage that occurred before 1995. If the latter it is hard to see what we can do about it now.

In fact the profile in 1995/96 can be evolved to the profile in 2005/06 without making the assumption that women are disadvantaged in appointments or promotions in that the number of women appointed as lecturers or promoted to senior lecturer or professor matches the number available in the pool from which they are appointed or promoted. The results of a model in which the percentage of women among researchers rises linearly from 24% to 30% and the percentage of women among appointments and promotions matches the percentage in the pool are shown in Figure 2. The results from the simulation for 2005 match the data rather well. (A detailed description of the model I used to produce the simulated 2005/06 figures is available at Google Docs.) This does not prove that women did not experience discrimination or disadvantage in appointments or promotion during the period 1995 to 2005. What it does show is that the data in Figure 1 do not, by themselves, show whether they did or they did not. Of course, discrimination or disadvantage must have occurred before 1995 in order to have a starting profile that was skewed to lower grades in the first place, but I was not aware that there was any dispute about that.

In the US the National Academies Report: Gender Differences at Critical Transitions in the Careers of Science, Engineering, and Mathematics Faculty (National Academies Press, 2009) found that there were gender differences in hiring. Women were more likely to receive the first job offer than they were to be asked to interview and more likely to be interviewed but the proportion of women applying was smaller than the proportion among those receiving Ph.D. degrees. Women were also more likely to receive tenure but the proportion of women candidates for tenure was smaller than the proportion of women among assistant professors. Because the data are snapshot data it was not possible to distinguish between the possibility that women are more likely to leave before coming-up for tenure and the possibility that the numbers of women being hired as assistant professors had increased in recent years. There were no gender differences in promotion to full professor. Studies of this kind that examine the transition processes with large enough data sets to reveal differences are what is required to reveal whether and when women are disadvantaged.

Women's Awards

One of the blogs I follow is femalescienceprofessor. Recently she posted questioning the necessity for awards recognizing the achievements of women in science, noting that she herself would have felt that the message from receiving a women-only award, had she been nominated, would have been ‘You’re a pretty good scientist, for a woman.” She does distinguish between awards intended to support women’s careers by making sure they are not at a systematic disadvantage and awards for achievement.

I have some sympathy with this view. However, some women-only awards do raise the profile of women in science.

Are women-only awards patronizing or do they serve a useful purpose? (One commenter’s response was ‘Yeah, I would take the money, wherever it came from.’)

Listening Skills

There is a blog called The Benshi by Randy Olson, a marine biologist turned filmmaker. One of his posts is about scientists’ inability to listen and why it can make science communication ineffective. I mentioned this inability to listen to another scientist who immediately thought of scientists’ behaviour in seminars, where, frequently, scientists are only listening in order to make their own points at the end.

I had been puzzled by the phenomenon where, at the end of a seminar, someone, usually a man, gets up and rambles on using up most of the question period on a subject of tangential relevance to that of the seminar, until I came across Ms. Mentor’s explanation. This phenomenon is called ‘peacocking’ and is a display behaviour. (I first read this in the report of a workshop on Gender Issues in the Sciences held at Colby College in Maine in 2003. The report of this workshop is available at http://www.colby.edu/~bbrown/2003Workshop.html. Emily Toth’s paper, ‘Successful Strategies for Advancement’ is on pages 22-23 and the longer transcript of her workshop starts at page 60.)

Our discussion turned to graduate student seminars. The other scientist described what happened in one department where, at question time, Prof. A. would ask the student giving the seminar a devastating question and Prof. B. would follow-up ‘like a hyena with a carcase after the lion has made the kill.’ The point of this style of questioning is to discover which students ‘have the balls’ to progress in science. There is no doubt that coping with hostile questioning is something that scientists have to learn. Is this really the best way to ensure graduate students acquire that skill? Could there possibly be gender-bias in which students are weeded-out?

Over Interpreted Data 2

My second example of over-interpreted data (that is, facts that do not support the inferences that people attempt to draw from them) is from the Campaign for Science and Engineering in the UK Policy Document Number 8, May 2008, Delivering Diversity: Making Science & Engineering Accessible to All (available as a pdf). The statement is:

‘A 2005 survey of STEM workers in Higher Education, found that 41% of men had been interviewed by all male panels compared with 27% of women. This illustrates the importance of making sure that interview panels are appropriately diverse.’

The first question might be 41% of what and 27% of what? It makes a difference whether it is 7/17 = 41% and 3/11 = 27% or 410/1000 and 135/500.

The figures appear to be taken from the Athena Project Report Number 26: ASSET 2003: The Athena Survey of Science Engineering and Technology in Higher Education (available from www.athenaforum.org.uk/reports), which states, referring to appointment to a first lectureship:
‘

Of those appointed in the last two years, 35% of the men and 26% of women had been appointed by all male interview panels, an improvement on the past:
• 3 to 5 years ago - 41% of men and 28% of women were appointed by all male panels
• 6 to10 years ago - 55% of men and 28% of women were appointed by all male panels.’

Table A8 of the Appendix to Report 26 - Statistical Tables gives the numbers of those who reported having an all male interview panel by grade and gender and Table 4 gives the total numbers of respondents to the survey by grade. From these we can establish that out of 1,512 male survey respondents 606 (40%) reported an all male interview panel and out of 660 female survey respondents 200 (30%) reported an all male interview panel. These numbers show that it is statistically very unlikely that the categories (male, female) and (reported an all male interview panel, did not report an all male interview panel) are independent. There are at least four possible explanations for this observation:

1. All male interview panels exhibit bias in favour of men.
2. Women are likely to be put off accepting positions if they meet no or few women during the recruitment process.
3. Women perform less well at interview if there are no women on the interview panel.
4. Women are not uniformly distributed among different subjects (see Table 3 in the Statistical Tables). Subjects with few women may be more likely to have all male interview panels and a preponderance of male appointees.

In options 1-3 an all male panel affects the selection process. In option 4 the association of male interview panels with male appointees is a result of a common factor, namely the relative numbers of women in different subjects. Unfortunately the data as presented in the Athena Report do not allow us to distinguish between these possibilities.

My point here is not that the composition of interview panels is not important. My point is that the data quoted do not, as is claimed, illustrate that importance. In fact, I have not been able to find any data relating to the effect of the composition of interview panels on the outcome of the appointment process. I found numerous exhortations to ensure that interview panels are appropriately diverse but no evidence that this makes any difference. (I tried Google and Google Scholar. If anyone knows where such data are to be found, please would you let me know?)

The data on unconscious bias show that it depends on the gender of those being evaluated not on the gender of those doing the evaluating (see Why so slow? The advancement of women by Virginia Valian,MIT Press 1999 ) It might be that having a women on the interview panel reduces the effect of unconscious bias but if that woman has had to be imported from another department it may reinforce it.

There is evidence that women are put-off by a recruitment process where the interview panel is all male or they meet no or very few women while visiting the prospective employer, at least in the graduate recruitment process (S.L. Rynes, R.D. Bretz, B. Gerhart (1991), "The importance of recruitment in job choice: A different way of looking", Personnel Psychology, Vol. 44 pp.487 - 521. digitalcommons.ilr.cornell.edu).

Irrespective of whether there exist data showing that the gender composition of interview panels affects the outcome of recruitment, if we are genuinely trying to attract a diverse workforce we would ensure that both interview panels and the people that candidates meet during the recruitment process are visibly diverse. Surely we would want the people coming to interviews, our potential colleagues, to feel welcome and to see that our jobs are not restricted to white men (or, in the non-academic context, white women).