Research dynamics and part-time work: an ecological model for factors driving gender imbalance in science and engineering.

Press release: The academic jungle: ecosystem modelling reveals why women are driven out of research. DOI: 10.1111/j.1600-0706.2012.20601.x
A large proportion of women and a growing number of men wish to work part-time in order to balance the demands of family and work.  However part-time employment in academia remains rare, and role models successfully balancing both teaching and research activities, are exceedingly rare.    There is a need to make part-time work more accessible and more viable in academia, in order to attract and retain more women in science and engineering research.   This paper identifies some of the most common and difficult issues faced by those working part-time in academia, and provides guidance about how to navigate around these.   It also identifies barriers faced by part-time academic staff which need to be addressed at a university level.

Assessing research performance of part-time staff is particularly difficult. Increasingly, research performance is assessed using metrics (such as number of papers, number of citations, h-index etc).   Application of these metrics can promote research output within an organization, however they can also undermine diversity.   In particular, research metrics are strongly biased towards full-time continuous employment, and penalize academics who take time off before becoming well established in their fields; e.g. women who part-time while raising their families.  This paper outlines the mechanisms by which metrics undermine the ability of women to participate in research if they work part-time.  This is done through an ecological analogy; just as a species is only sustainable if its population exceeds a minimum critical threshold, so too do researchers need to exceed a critical mass in order to attract more funding, students and high quality collaborators and so maintain their productivity.  In addition, the research production rate, analogous to the population birth rate, needs to exceed a critical rate if the population is to grow and survive –  these higher production rates are harder to achieve when part-time . A lower production rate is usually assumed to have a proportional effect on research outputs, but the ecological model suggests far more complex consequences on overall research productivity. If women have children before they are well established in their field, our model suggests that they will struggle to remain competitive.   This explains the observed drift of women from research to teaching, where performance is assessed on current rather than accumulated historical performance.

There are further analogies between ecosystems and universities: in both cases, diversity underpins resilience.  Optimizing a system, whether it be a forest or a faculty, to a narrow set of criteria is likely to undermine the ability of that system to respond to disturbance.   In the case of universities, over-reliance on research metrics could undermine the long-term quest for excellence by reducing the pool of talent from which our researchers are drawn.

The authors provide clear advice on how to address these issues:

• part-timers should be strategic and concentrate on either research or teaching; they need wise mentoring, and need to brave to be the “odd ones out” in a system overwhelming dominated by full-time continuous employment.
• university managers should use metrics cautiously, and implement schemes to ensure that part-time work and career breaks are not “one-way tickets” out of research.