Chapter 7. Gender in a changing context for STI
The under-representation of women in certain areas of science, technology and innovation (STI) has long been a concern. As the benefits of diversity in STI – both in terms of research excellence and relevance – become clearer, most countries are implementing policies to try to address gender equity. However, issues such as gender stereotypes and evaluation bias are embedded in research systems, and are resistant to simple interventions. This chapter begins by looking at the key issues affecting gender equity in science at different life stages. It starts with gender stereotypes that influence educational choices and career expectations in early childhood. It follows with a discussion of undergraduate and graduate education, as well as gender issues in research careers and the research system. It then considers the changing context for STI, and how this increases the emphasis on diversity. Finally, it lays out a future vision for a more diverse and productive scientific enterprise. While acknowledging that most countries have included gender diversity as one of the key objectives in their national STI plans, the chapter argues that policy initiatives remain fragmented. A more strategic and systemic long-term policy approach is necessary.
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
An estimated USD 12 trillion (US dollars) could be added to global gross domestic product by 2025 by advancing gender parity (McKinsey, 2015); this alone provides a strong rationale for including gender issues in STI policy. However, the benefits of tackling the under-representation of women in STI go well beyond economic gains and access to talent. In addition to the important issues of social justice and fairness, growing evidence suggests that diversity improves the quality of research and the relevance of its outcomes for society (Smith-Doerr, Alegria and Sacco, 2017). It is not surprising that gender has figured on STI policy makers’ agendas for several decades and is now receiving even greater attention in most countries, with the expectation that STI will make a major contribution to the Sustainable Development Agenda 2030 and the 17 Sustainable Development Goals (SDGs). Not only does a specific goal (SDG 5) target gender, but diversity and inclusiveness in STI are considered a prerequisite for producing the types of knowledge and innovation required to respond effectively to all the SDGs.
In 2006, OECD published a report Women in Scientific Careers: Unleashing the Potential that took stock of the gender imbalances in different scientific fields and at different career stages in both the public and private sectors. It reviewed the policy actions taken by governments to address these imbalances, and concluded that “few countries appear to have a comprehensive approach to promoting the participation of women in scientific education and research careers”. Since 2006, there has been some progress in some fields in some countries but the picture today remains largely the same as it was then (OECD, 2017a) and the same challenges prevail (Table 7.1). There are also some new issues related to gender bias in the selection of research topics and related innovations that were not much discussed a decade ago, but are increasingly recognised as important to STI policy.
Today, most OECD countries are implementing a variety of policy measures to address obvious gender inequalities (Box 7.1). Nevertheless, gender imbalances persist, and are particularly evident in some Science, Technology, Engineering and Mathematics (STEM) areas. While some policy measures – such as targeted support for individuals – are relatively easy to implement and assess, other areas such as changing gender stereotypes and eliminating implicit gender bias are much more resistant to intervention and require longer term cross-sectoral action.
The 2017 OECD/EC STI Policy survey reveals that almost all countries have implemented specific policy initiatives related to gender in STI (OECD, 2017b). Over 100 initiatives were reported, with several countries reporting multiple initiatives led by different institutions In almost all countries, gender equity is a strategic priority as identified in a variety of national plans. It is mainly addressed through targeted competitive funding – i.e. fellowships, project grants and prizes – for different stages of science training and career paths. Some countries have also attached conditions predicated on gender equity to the awarding of institutional funding. Several countries have also implemented public-awareness campaigns, e.g. schemes to support outreach by women scientists in schools. Fewer initiatives focus more precisely on the systemic issues – such as peer-review, reward and promotion mechanisms – that influence gender balance in academic institutions. The section immediately below provides some examples of how countries are combining multiple policy actions to address gender equity.
Australia: Gender equality is emphasised in the National Innovation and Science Agenda, 2015 and the Australian government is implementing a range of initiatives to support women’s participation in STEM studies and careers. The funding schemes of the Australian Research Council (ARC) are underpinned by policies to support gender diversity. All ARC schemes take into account any career interruptions as part of the assessment processes and part time work and parental leave are enabled in some schemes. ARC also provides each year two named Laureate Fellowships for female researchers to undertake an ambassadorial role to promote women in research. Several other research-funding agencies have also implemented mechanisms to promote gender equality and diversity, including adjusting the criteria for awarding institutional block grants that support PhD training; establishing a dedicated Women in Health Science Working Committee to monitor gender-balance issues; and targeted training initiatives in mathematics. In 2016, the inaugural programme of the Homeward Bound leadership initiative culminated in the largest ever female expedition to Antarctica1.
Germany: Only 24% of university lecturers and 15% of the country's 38 000 tenured professors in Germany are women. To improve those statistics, the German Education Ministry has introduced a Women Professors scheme, whereby the Ministry pays the salary of one to three female professors or lecturers at universities that are committed to redressing gender imbalances at the leadership level. The Government has committed substantial funds to its equal-opportunity programme for universities, with the aim of creating 200 additional posts for highly qualified female academics. Each post will be funded for five years, with the Federal Government and the individual states (Länder) splitting the costs. To secure the funding, the universities had to submit plans demonstrating their commitment to promoting more women to top academic positions and sustainably restructuring the university.
Ireland: Starting in 2013, the Ireland Research Council, the Higher Education Authority and Science Foundation Ireland have emphasised the need for a consistent and concerted approach to gender issues. Specific actions to this end include changing the eligibility criteria for the Starting Investigator national grant programme to increase the number of women applicants, and directing institutions to adopt the Athena Scientific Women’s Academic Network (SWAN) award accreditation as a mandatory requirement to receive research funding. [The Athena SWAN Charter is an internationally recognised “quality mark” for gender equality administered by the Equality Challenge Unit in the United Kingdom. A similar accreditation, the Juno Excellence award, focuses on physics and is managed by the UK Institute of Physics.]
Japan: Women account for fewer than 15% of all researchers in Japan. The Japanese Government has taken several policy measures to address the cultural norms and practices driving this imbalance. Since 2006, a scheme to “support girl students to choose a science course” sponsors events where schoolgirls meet and talk with women scientists and engineers. In 2015, the Government implemented a new initiative to “realise diversity in the research environment”, by supporting women researchers with family and care responsibilities.
Mexico: Mexico is implementing several initiatives to promote diversity and inclusion in STI, including the Mexican Mothers Heads of Households Scholarships, aimed at single, divorced, widowed or separated mothers who are pursuing professional studies (technical specialisation or third-level degree) in public higher education institutions; and the Scholarship Programme for Indigenous Women, which provides support for postgraduate studies in Mexico or abroad. Dedicated funding is also available for research projects that can generate knowledge, technological developments or innovations addressing women’s issues and needs.
Source: OECD (2017b), EC/OECD STI Policy survey, https://stip.oecd.org/stip.html.
Several trends – including globalisation, the internationalisation of higher education, increasing researcher mobility, and new paradigms of open science and inclusive innovation – are changing the landscape in which gender, STI and socio-economic conditions interact. This is generating both new challenges and new opportunities for women in STI. The shifting context heightens the need for a greater understanding and acknowledgement of how gender inequalities are created and perpetuated in science institutions, within scientific research, and when translating scientific knowledge into innovation. While the availability of sex-disaggregated data for socio-economic analyses has been improving, better data and new indicators are needed to monitor the evolving situation and inform appropriate policy interventions that address the causes as well as the symptoms of gender inequality in STI.
This chapter begins by looking at the key issues affecting gender equity in science at different life stages. It then considers the changing context for STI, and how this increases the emphasis on diversity. It starts with gender stereotypes that influence educational choices and career expectations in early childhood. It follows with a discussion of undergraduate and graduate education, as well as gender issues in research careers and the research system. Finally, it considers the main drivers for change in STI, and lays out a future vision for a more diverse and productive scientific enterprise. It is difficult to do justice to all the important aspects of gender equality in STI in a single short chapter; hence, some important issues are referenced, but not discussed in detail.2 The chapter does not make a strong distinction between scientific careers in the public/academic sector and the private sector: although differences exist, the key issues affecting gender equity are very similar. The chapter also does not deal in depth with some specific issues relating to gender and innovation, although they are recognised as an increasingly important area for policy development.
The relative over-representation of men in STEM starts at an early stage and is reflected in the numbers of men versus women in school subjects, types of education and degree programmes. While some debate is taking place as to what exactly causes these gender differences, the evidence points to stereotypes more than capabilities (Miller, Eagly and Linn, 2015). Interestingly, the numbers of men and women vary depending on disciplines, countries and cohorts. This indicates there are structural, cultural and socio-economic factors at play, rather than inherent, unchangeable factors.
Gender stereotypes are common expectations about the roles of men, women, boys and girls in society, at home and at work. These “received ideas” do not only reflect what men and women typically do, but also what they should do, and are therefore normative and prescriptive (Heilman, 2012). The main expectation is that men work and women care, and that men have a higher innate ability for most STEM fields than women (Leslie et al., 2015). The visible division of labour at work and at home is “justified” by inherent biological differences. Making counter-stereotypical “choices” is therefore harder and generates more disapproval than fitting the stereotype.
Stereotypes are acquired at an early age – even before schools starts. From age six or so, both boys and girls say that boys are more likely to be “really, really smart” than girls (Bian, Leslie and Cimpian, 2017), and both boys and girls are more likely to draw a man than a woman when asked to “draw a scientist” (Miller et al., 2018). These stereotypes generally intensify during adolescence (OECD, 2018a), and are reinforced at key stages over the life course, including marriage, childbirth and ageing/caring. Understanding the cumulative effects of stereotypes on individual choices and careers is one reason why the ability to measure the persistence rates of women in STEM is important (Section 4).
The finding that countries scoring highly on gender equality, as measured by the Gender Gap Index,3 number fewer women in certain STEM areas is most likely related to internalised gender stereotypes (Charles, 2017). Gender stereotypes are socially and culturally embedded, and resistant to simple policy actions. Although a growing number of evidence-based policy measures are being developed, persistent gender stereotypes in the media - including social media - and advertising may counter or even cancel out the positive effects of these interventions (European Parliament, 2014). Children think they cannot be what they cannot see; reproduced stereotypes inhibit their motivation, ability and self-efficacy, and ultimately restrict their choices. Thus, gatekeepers to STEM careers – parents, teachers, career counsellors, future employers – need to work together with policymakers to prevent gender stereotyping of jobs and skills (Box 7.2).
Overcoming stereotypes of what men and women do at home and at work (particularly in STEM professions) is possible. However, the process needs to start early in life, and to be regular and consistent. Occasional exposure to the counter-stereotype may simply reproduce the norm, on the premise that “the exception proves the rule”. Several examples of evidence-based interventions addressing gender stereotypes in STEM exist in both educational institutions and the media.
Primary education:
The #RedrawTheBalance campaign by Education and Employers (United Kingdom) started from a project asking children to draw their future profession, which revealed both a limited view of their possible future and the existence of gender stereotypes. Subsequently developed interventions include Inspiring the Future4 and Primary Futures.5,6
The Young Scientists Australia programme is one of many initiatives that engage and challenge young children to explore and invent, with inspirational assignments from different STEM fields.7 A similar programme, Let Toys be Toys, was developed in the United Kingdom to support teachers in challenging stereotypes in the classroom.8
Secondary education:
Efforts to engage girls in coding and other aspects of computer science are often driven jointly by information and communication technology (ICT) companies and non-governmental organisations (NGOs) or government agencies. One far-reaching example with a strong social media presence is the US-based Girls Who Code.9
Various initiatives are being developed in local settings to attract and sustain girls’ interest in physics. These include: “girls’ days” organised at German physics research institutes, such as Deutsches Elektronen-Synchrotron;10 classroom interventions developed by the UK Institute of Physics;11 and an Italian school competition for developing a video or interactive website that changes stereotypes of women in the natural sciences.12
Finally, the Hypatia project has put together an evidence-based toolkit in various languages, with resources and national knowledge hubs to promote gender-inclusive STEM education in schools, science centres and museums across the European Union.13
Media representation and advertising
The Dutch NGO WOMEN Inc. has launched a campaign, #BeperktZicht (“limited vision”) and established a coalition with media partners. The goal is to improve the representation and inclusion of women and ethnic minorities in the media, not only by increasing numbers, but also by featuring them in more counter-stereotypical roles.14
In 2016, the US Government developed a factsheet for media partners depicting STEM opportunities (including for women) as part of STEM 2026. This “aspirational vision for STEM education” is inspired by the so-called “Scully effect” (in reference to the popular TV series “The X-Files”) of growing interest from girls in science, medicine and especially forensics.15
The United Nations recently launched a global initiative to eradicate harmful gender stereotypes from advertising. The Unstereotype Alliance brings together leaders from business, technology and the creative industries around a joint commitment to foster inclusive communication.16
Undergraduate level
Higher education systems have expanded considerably in recent years, leading to a growing number of students and graduates, including more women. In many countries, the share of women completing tertiary education has grown faster than the share of men. In Europe, the share of 30- to 34-year-olds having completed tertiary education grew steadily, from 24% to 39 % over 2002-16. Growth was considerably faster for women, who in 2016, were at 44 %. In contrast, for men the share was 34%.17
In science education, women and men are unequally distributed across academic courses. Women have traditionally dominated in the social sciences and humanities, and are increasingly dominating in the life sciences and medicine, whereas men prevail in other STEM areas (Figure 7.1). These differences seem to largely reflect cultural stereotypes.
Source: OECD (2017d), Education at a Glance 2017: OECD Indicators, https://doi.org/10.1787/eag-2017-en.
Historically, the under-representation of women in STEM has received much greater attention than the under-representation of women in philosophy or economics, or the under-representation of men in psychology, veterinary sciences or nursing. When assessing the effect of efforts to attract more girls into STEM bachelor programmes, it is important to consider the disciplines separately (Figure 7.1). “Stuffing the pipeline” only helps when there is a future to be found in these fields upon graduation (Miller and Wai, 2015).
Efforts to address women’s under-representation in STEM are shaped and constrained by the manner in which the problem is framed, which needs to be sensitive to evolving contexts. For example, if it appears that more girls are not attracted to engineering because they are unaware of the opportunities or do not understand the nature of engineering work, then corrective actions should focus on outreach and informing them of the opportunities offered by engineering careers (Beddoes, 2011).
Furthermore, it is necessary to (re)consider how entry into certain higher education fields may be biased by reliance on standardised tests. For example, the Scholastic Aptitude Test scores commonly used for college admissions in the United States have been show to under-predict women’s academic performance and over-predict men’s, and test score differences do not necessarily translate into meaningful professional distinctions (Nature Editorial, 2005). Finally, if gender gaps in participation and performance are mutually reinforcing, educators seeking to promote women should address both factors simultaneously to maximise student achievement (Ballen, Salehi and Cotner, 2017). The small minority of female students who choose to enter some STEM fields may need mentoring and peer support – e.g. through networks – to perform optimally.
PhD level and early-stage careers
The doctoral level is the only educational level with near gender parity: all fields considered, 3.0% of men and 2.9% of women on average enter a doctoral programme across EU countries (Figure 7.2). In practice, however, this means that the share of women in higher education declines at the postgraduate level, particularly in STEM fields. Nevertheless, the share of women in certain STEM fields has significantly increased over time, and the leaky pipeline between graduate and postgraduate education and training is no longer a major challenge (Miller and Wai, 2015). For example, only 14% of US doctoral degrees in biological sciences were awarded to women in 1970, compared to 49% in 2006. In 2015, more women in Europe received a PhD degree in life sciences than men. Entry into other STEM areas has been slower, but substantial. For example, 5.5% of US doctoral degrees in physical sciences were awarded to women in 1970, compared with 30% in 2006; 8% of US doctoral degrees in mathematics and statistics were awarded to women in 1970, compared to 32% in 2006 (Hill, Corbett and Rose, 2010).
There is growing concern that there are not enough jobs in academia for the rapidly growing population of PhD holders, although the potential scale of this issue varies across countries (Figure 7.2). Early-stage researchers often hold precarious positions in a very competitive environment: their academic careers begin with fixed-term contracts, often based on project funding. Hyper-competition, and its reinforcement of assertive and self-assured stereotypes, serves as an exclusionary mechanism for those who cannot or will not compete continually. The choice to enter this competition coincides with “the rush hour of life”, i.e. establishing partnerships and families, which tends to reinforce gender imbalances.
Source: OECD (2017c), OECD Science, Technology and Industry Scoreboard 2017: The digital transformation; https://doi.org/10.1787/9789264268821; based on OECD/UNESCO data collection in OECD/UNESCO (2017), Careers of Doctorate Holders 2017, http://oe.cd/cdh; OECD (2017d), Education at a Glance 2017: OECD Indicators, https://doi.org/10.1787/eag-2017-en; OECD (2009), Education at a Glance 2009: OECD Indicators, https://doi.org/10.1787/eag-2009-en.
The precariousness of academic careers reduces the attractiveness of research for new and talented entrants, who can find more secure and better paid employment elsewhere (European Science Foundation [ESF] EUROAC, 2015; Janger et al., 2017). Women scientists, especially at the early career stage, are generally far less satisfied with their social and job security than men. This can be at least partially related to individual and societal expectations about motherhood and family structures. The share of female researchers with children is lower than for male researchers; this is especially true for researchers working in full-time positions. At the same time, the share of part-time working mothers in research is higher than the share of part-time working fathers (Janger et al., 2017). These divisions reflect the overall unequal distribution in society of care (including elder care) responsibilities between women and men. Targeted policies addressing employment conditions are required to address this, including through: flexible working practices; availability of parental leave, paternity leave and childcare facilities; dual-career opportunities for couples; flexible pension plans; and opportunities for career breaks (EC-PPMI, 2016). To be effective, however, flexible employment conditions need to be accompanied by “compensatory” measures with regard to performance evaluation, e.g. extended eligibility windows for tenure.
Efforts to increase the numbers of women studying STEM at the undergraduate and doctoral levels have not translated into equal or equitable representation of women in senior STEM positions. Various analyses within particular disciplines and/or national settings indicate this phenomenon will not simply resolve itself over time as more women enter STEM education. Other explanations need to be considered to understand why women’s careers in STEM progress more slowly, stall more often and are more likely to be discontinued than men’s (ESF, 2009; European Commission, 2015; National Science Foundation [NSF], 2017).
To identify levers to achieve gender equality, it is necessary to 1) track research careers across disciplinary, national and sectoral borders; and 2) gain a better understanding of the causes and consequences of different types of mobility between positions, both within and across institutions (Box 7.3). Researcher mobility is generally considered a good thing, which should be encouraged; the evidence shows that researchers who are mobile produce more highly cited research (OECD, 2017b). Yet it is easy to see how an over-emphasis on mobility could inadvertently disadvantage women at various life stages. In Europe, it takes an average of 17 years after obtaining a PhD to reach the most senior level in research (Janger et al., 2017). Despite some efforts to map research careers (ESF EUROAC, 2015; Janger et al., 2017), understanding exactly how they develop in terms of patterns or moves through positions, institutions, sectors and national borders remains largely uncharted territory. No quantitative gender-segregated data exist on the career paths and working conditions of researchers (MORRI, 2015).
Recent overviews of the position of women in STEM such as European Commission’s SheFigures (European Commission, 2015) and NSF (2017) use various statistical indicators to show the relative representation of women within a given professional category or career stage. The OECD STI Scoreboard also collects a number of STI indicators, which can be disaggregated by gender (OECD, 2017b). These combined sources of information give a good overall picture of the gender balance in STEM. As discussed in this chapter (Section 3.2), one of the major challenges for women who enter into scientific careers is career progression. However, current indicators are typically static and do not inherently indicate career progress. Even if representation changes at various career stages and/or over time, this difference or change cannot be said to unequivocally reflect actual career development, hence the need for an indicator that reflects career progress or development within STEM professions over time. Such indicators have already been developed for other professional fields and could be adapted to reflect the specificities of STEM careers (Dries et al., 2009).
Developing a career-progression indicator for STEM is feasible, because research careers around Europe and North America reflect a highly comparable logic of four to five consecutive levels – from PhD to full professor or senior researcher, with minimal disciplinary and institutional variations*. Often, the dominant career system reflects an up-or-out dynamic, with a permanent contract only achieved after reaching a certain level within a limited amount of time.
Such an indicator would make career progress quantifiable and comparable. It would help track gender, national or disciplinary differences and similarities between careers, and could shed light on the actual movement of researchers across positions and institutions. Together with existing statistical measures, it could inform policy making on research careers at the international, national and institutional levels.
*The five career levels are described in the report of the ERCAREER project (2012-14), funded by the European Research Council to study “the paths and patterns, differences and similarities in the career paths of women and men ERC grantees”18.
It is important to recognise that research careers do not necessarily progress within academia: research and development (R&D) positions in both the private and public sectors provide growing employment and career opportunities for PhD holders (Figure 7.3). In some countries, more women researchers are employed outside of academia than within (OECD, 2017a). Although industry generally lags behind the public sector as regards gender equity in the research workforce, there is growing recognition this has negative economic consequences (Peterson Institute, 2016). Several leading corporations have recently adopted strategies to boost the representation of women in engineering manufacturing, information technology and product management. In 2016, the Anglo-Australian mining company BHP announced its intention to reach 50/50 gender representation among its 65 000 employees; in February 2017, General Electric announced its goal of achieving 50/50 representation for all entry-level technical programmes and hiring 20 000 women to fill STI roles by 2020. For researchers – especially women – toiling in precarious post-doc positions in academic settings, these “outside opportunities” may offer better career prospects than academia, combined with more security and flexibility. Thus, creating opportunities for inter-sectoral mobility at all career stages (and monitoring this mobility) could be an important contributor to increasing overall research productivity, while at the same time promoting gender equity.
Source: OECD (2018b), OECD Main Science and Technology Indicators, www.oecd.org/sti/msti.htm (accessed on 18 June 2018).
Gender differences in scientific careers are not only apparent in representation and advancement, but also in pay and decision-making power. As reported in European Commission (2014), the hourly wage difference in the scientific R&D area is around 18% and widens with age (see also OECD, 2017a). Similarly, only around 20-25% of board members and heads of research institutions are women. Sullerot’s Law19 seems to apply here: as the representation of women in particular STEM fields, professions and hierarchical levels rises, overall pay levels and status drop (Levanon et al, 2009).
The evaluation of performance plays a central role in the functioning of research systems. In academic settings, this principally includes peer review of publications and grant proposals, and national research and teaching assessment exercises. Often, such evaluation boils down to an assessment of individual rather than team performance, with principal investigators and corresponding authors endowed with the highest status, and obtention of individual grants and prizes considered more prestigious than participation in large-scale collaborations. These evaluations, in turn, help determine individual promotion and tenure awards.
Individual performance evaluation is very susceptible to gender bias – which, strictly defined, refers to a cognitive distortion that affects decision-making. Gender bias is linked to gender stereotypes, which perceive a better fit between men’s innate abilities and STEM compared to women (Leslie et al., 2015). As a result, women working in STEM are “presumed inherently less competent” (Saini, 2017), leading to shifting standards in performance and merit evaluation. Gender bias affects progression in research careers, by limiting women’s chances of being promoted. It is deepened by (impending) motherhood, effectively making it even harder for women to fit the stereotype (although men with care responsibilities also often suffer from “flexibility stigma” in research institutions). The relative absence of women in senior positions helps reinforce the stereotype. As gender bias is often implicit and subtle, it is more difficult to recognise and acknowledge – and thus harder to counter than blatant and explicit discrimination (Biernat, Tocci and Williams, 2011).
Bias is prominent in the construction, operationalisation and application of evaluation criteria (Vinkenburg, 2017). It is especially pronounced in systems that rely on peer review (from recommendation letters to evaluations of grant proposals), but citations, student evaluations, journalists’ quotes and questions asked at conferences tend to be equally biased in favour of men (Saini, 2017). In a research system that is inherently founded on merit, it is hard to prove that reward allocation and performance evaluation practices often result in an unequal distribution of success in favour of some compared to others, regardless of the actual distribution of merit. Nevertheless, the development and adoption of interventions to effectively mitigate bias is growing (Box 7.4).
While many research organizations turn to implicit or unconscious bias training, there is only limited research evidence on the impact of this kind of training. However, there are some evidence based design specifications for systemic diversity interventions engaging “gatekeepers” or decision makers in mitigating the effects of gender bias in performance evaluation (Vinkenburg, 2017). These specifications take into account the target group, length, focus, behavioural nature, and structured nature of the interventions. Examples are given below.
Breaking the bias habit®, University of Wisconsin (United States) and funded as part of the NSF ADVANCE programme: this short training programme has had a proven impact on attitudes and behavioural intentions among faculty members, with the result that significantly higher numbers of women have been hired and promoted20 (Devine and Carnes, 2017).
Monitoring gender equality, Swedish Research Council (Vetenskåpsradet): the Council performs active monitoring, using participant observation of research panels and feedback on meeting practices, to improve the application and success rates of women in research funding; two reports were published in 2013 and 2015.21
Training video for selection committees and panel members in research organisations: developed by CERCA Institute (Spain),22 this training video is now used by the European Research Council.23
Bias interrupters, CWLL (United States): this website features practical tools to help organisations and individuals interrupt bias in performance evaluation, recruiting, assignments and compensation24 (based on Williams, Philipps and Hall, 2016).
Gender-blindness in research and innovation is both a symptom and a cause of the under-representation of women in STEM, particularly at senior levels. Research priorities and agendas are largely established by men, and research design and resultant innovations may fail to consider gender specificities (Box 7.5). In extreme cases, the lack of attention to gender considerations when translating scientific knowledge into products or actions can actually be harmful to women.
The issue of gender in the context of STI goes beyond improving the number of women scientists, inventors and innovators: it influences the relevance and quality of research and innovation outcomes for women and men.
The traditional “gender-blind” approach to STI assumes that research results are applicable independently of the researcher or intended end-user’s gender. However, there exists a strong gender dimension to the choice of STI topics, and the way research is conducted and translated into innovations. Gender bias permeates important fields of scientific knowledge, with more evidence relating to men than to women. For example, much medical research has been done exclusively on male experimental models and men, and then extrapolated at the level of medical practice to the whole population, with little regard for the biological differences between the sexes. Innovations, including new technologies, tend to be determined by masculine norms.25 “Gender-blind” research and innovation can be harmful to women. It can also miss important opportunities to create new markets for products – e.g. in health care – that utilise scientific knowledge of sex/gender differences (Pollitzer and Schraudner, 2015).
A particular concern in relation to gender-blindness is the growing use of artificial intelligence (AI) and algorithms in STI. AI systems depend on training based on very large data sets (e.g. of images), which themselves often reflect societal gender stereotypes and inherent biases. There is a widespread assumption that algorithms – as opposed to human judgements – are objective and free from discrimination. In practice, the use of algorithms and AI can inadvertently perpetuate existing biases, and discriminate more consistently and systematically on a larger scale (O'Neil, 2016; Bolukbasi et al., 2016). Collecting evidence and raising awareness of the potential for digital discrimination in STI are important first steps in ensuring it does not propagate. On a more positive note, the potential also exists to harness “gender-neutral” AI to help eliminate gender bias in research evaluation (Erel et al., 2018).
Most OECD countries recognise that the topics and conduct of research, and its translation into innovation, are often gender-blind. New governance arrangements, rules, guidelines, regulations and targeted funding schemes are being introduced to redress these inherent biases. In Korea, amending the Key Framework Act on Science and Technology (2009) to formally acknowledge the importance of gendered innovation is one of several measures being taken to implement a new science and technology plan “with and for the people”. In Spain, a new national award for gender equality is being launched in 2018, with the dual aims of promoting gender equity, and integrating the gender dimension into research and innovation content in public research institutions. France has a similar dedicated financial-support mechanism for institutions that incorporate gender in their research content. Denmark has developed a broad agenda to systematically include relevant gender perspectives in research. Finally, the United Kingdom is funding multidisciplinary research on digital discrimination and gender.
The scale and pattern of international collaboration in STI has grown massively over the past two decades, driven by digitalisation and the emergence of new scientific powerhouses outside of the OECD. Similarly, higher education is increasingly a global enterprise, with international universities in many parts of the world educating large numbers of overseas students. As discussed, gender balance in science varies considerably across countries, despite their increasing interconnectivity and interdependence. Policy actions to promote international exchanges of female STEM students and the mobility of female researchers are one mechanism to redress some of the current imbalances. Within Europe, this is facilitated by dedicated European Commission funding schemes. Such mechanisms also exist at the bilateral scale: for example, a France-Morocco partnership has recently been established to strengthen the role of women in scientific research.
Globalisation, interconnectivity and technological development are not just affecting science and education, but are also fundamentally changing socio-economic systems. This leads to new and complex challenges, which in turn require new scientific approaches, as illustrated by the Paris accord on Climate Change and the United Nations SDGs (Section 1). Responding effectively to environmental change and meeting the SDGs will require integrating knowledge from many distinct scientific domains, and applying transdisciplinary research approaches that engage end users in the co-design and co-production of research. Natural and social scientists will increasingly need to work together, often in large transnational teams.
Another factor that is dramatically affecting research practice is digitalisation, which has enabled open science and data-driven science, with major implications for the future scientific workforce. Not surprisingly, policy often focuses on the core ICT professions or disciplines; the gender imbalances in these areas are certainly very substantial and need to be addressed (OECD, forthcoming). At the same time, digitalisation is transforming professions such as librarianship and archiving, where women are better represented. Opportunities exist to raise the status and reward for these professions, which are essential to developing the digital data services on which science will increasingly depend. Australia, for example, has identified re-training librarians as a major pillar of its digital skills for science strategy. The policy emphasis on open science and collaboration also implies that science communication, team building, ethics and legal knowledge will become more important to the scientific endeavour. This will present opportunities to design and reward academic careers differently, and provide more options for women (and men) wishing to contribute to science.
Globalisation, complex societal challenges, open science and digitalisation all have one commonality – they emphasise the need for greater diversity in STI. While diversity considerations in science are not limited to gender, it is a cross-cutting issue that applies to all population groups. Women and men may differ in biology and behaviour, but they are also similar in many respects. Beyond the “binary” classification, the concept of “gender diversity” encompasses the differences deriving from the interactions between the biological, ethnic, cultural or psychological characteristics that individual women and men develop over their life course. These interactions are the subject of active scientific research, including on developing methods to measure and compare differences between individuals and groups. Nevertheless, it is generally agreed that gender equality, combined with cultural and cognitive diversity, improves the quality of research and innovation outcomes (Abbasi and Jaafari, 2013; Campbell et al., 2013; Hinnant et al., 2012; Jeppesen and Lakhani, 2010). Hence, solutions-focused research and innovation needs to reflect the diversity of the societies in which the solutions will be situated.
The many reports on women in science tend to share a future vision for a world in which there are equal opportunities for women to enter, contribute and progress in all scientific disciplines without prejudice or bias. This implies a more diverse, productive and attractive research enterprise, which fully recognises and rewards the equivalent and distinct contributions of both men and women. Clearly, achieving this vision is still a long way off, which is further complicated by the major transitions that science and innovation are currently undergoing.
As discussed throughout this chapter, almost all countries are taking policy actions to promote gender equity in STI. These focus on feeding the pipeline for STEM subjects and providing support for individual women scientists at various career stages; some seek to address the underlying causes of gender imbalance, including gender stereotypes and inherent gender bias in science and innovation systems. However, the overall picture shows a fragmented approach, characterised by multiple institutions acting independently, and limited co-ordination between education, science and innovation actors. There is little systematic evaluation of the effectiveness and sustainable impact of the many interventions under way. In some cases, this will require developing new indicators and measures, presenting important opportunities for mutual learning across different countries and developing communities of practice.
Addressing gender inequalities in STI will require a strategic and systemic long-term approach. Policy actions are necessary on several fronts to: 1) continue to monitor and address long-term challenges in scientific education, training and careers; 2) ensure that digital education and training strategies provide full and equal opportunities to girls and women, and do not enforce traditional gender stereotypes or introduce digital discrimination; and 3) ensure that the contribution of all disciplines and supporting professions is fully recognised, valued and rewarded in the transition to open science and greater transdisciplinary research. There is a need for strategic thinking and targeted interventions that will create positive feedback loops to strengthen the position of women within STI systems as a whole (Figure 7.4). Co-ordinated actions engaging multiple actors – governments, research funders, academia, public research organisations, educational institutions and corporations – must be implemented at multiple levels, from local to global.
Source: Based on Bleijenbergh and Van Engen (2015)’s participative system-dynamic model of gender inequality at a technical university.
Looking to the future, diversity and inclusiveness will be critical to improving research productivity, and the relationship between science and society. Those countries, institutions and firms that achieve gender equity will be well placed to emerge as leaders in their fields. Policy makers have an important role to play in establishing and implementing the necessary regulatory and normative frameworks to achieve this, and will themselves need to fully embrace gender equality and diversity.
References
Abbasi, A. and A. Jaafari (2013), “Research impact and scholars’ geographical diversity”, Journal of Informetrics, Vol. 7/3, pp. 683-692, Elsevier, Amsterdam, https://doi.org/10.1016/j.joi.2013.04.004.
Ballen, C.J., S. Salehi and S. Cotner (2017), “Exams disadvantage women in introductory biology”, PLoS ONE, Vol. 12/10, Public Library of Science, San Francisco, https://doi.org/10.1371/journal.pone.0186419.
Beddoes, K.D. (2011), “Engineering Education Discourses on Underrepresentation. Why Problematization Matters”, International Journal of Engineering Education, Vol. 27/5, pp. 1117-1129, Dublin Institute of Technology Tempus Publications, Dublin, http://www.sociologyofengineering.org/wp-content/uploads/2016/01/Beddoes-IJEE-2011.pdf.
Bian, L., S.-J. Leslie and A. Cimpian (2017), “Gender stereotypes about intellectual ability emerge early and influence children’s interests”, Science, Vol. 355/6323, pp. 389-391, American Association for the Advancement of Science, Washington, DC, https://doi.org/10.1126/science.aah6524.
Biernat, M., Tocci, M.J. and Williams, J.C. (2011), “The Language of Performance Evaluations: Gender-Based Shifts in Content and Consistency of Judgment”, Social Psychological and Personality Science, Vol. 3/2, pp. 186-192, https://doi.org/10.1177/1948550611415693.
Bleijenbergh, I. and M.L. Van Ergen (2015), “Participatory modeling to support gender equality”, Equality, Diversity and Inclusion: An International Journal, Vol. 34/5, pp. 422-438, Emerald Group Publishing, Bingley, United Kingdom, https://doi.org/10.1108/EDI-06-2013-0045.
Bolukbasi, T. et al. (2016), “Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings”, 21 July 2016, arxiv.org, Cornell University, Ithaca, NY, arXiv:1607.06520v1 [cs.CL].
Campbell, L.G. et al. (2013), “Gender-Heterogeneous Working Groups Produce Higher Quality Science”, PLoS ONE, Vol. 8/10, Public Library of Science, San Francisco, https://doi.org/10.1371/journal.pone.0079147.
Charles, M. (2017), “Venus, Mars, and Math: Gender, Societal Affluence, and Eighth Graders’ Aspirations for STEM”, Socius, Vol. 3, Sage Publications, Thousand Oaks, CA, https://doi.org/10.1177/2378023117697179.
Devine, P.G. and M. Carnes (2017), “A gender bias habit-breaking intervention led to increased hiring of female faculty in STEMM departments”, Journal of Experimental Social Psychology, Vol. 73, pp. 211-215, Elsevier, Amsterdam, https://doi.org/10.1016/j.jesp.2017.07.002.
Dries, N. et al. (2009), “Development and validation of an objective intra-organizational career success measure for managers”, Journal of Organizational Behavior, Vol. 30/4, May 2009, pp. 543-560, Wiley-Blackwell, Hoboken, NJ, https://doi.org/10.1002/job.564.
EC-PPMI (2016), Research Careers in Europe: Final report. Prepared by the PPMI Group, CARSA and INOVA for the European Commission, European Commission and Public Policy Management Institute, Brussels and Vilnius, https://blacksea-horizon.eu/object/document/618/attach/NC0614200ENN_002.pdf.
Erel, I. et al. (2018), “Selecting Directors Using Machine Learning”, NBER Working Paper, No. 24435, National Bureau of Economic Research, Cambridge, MA, http://papers.nber.org/papers/w24435?utm_campaign=ntw&utm_medium=email&utm_source=ntw.
ESF (2009), Research Careers in Europe Landscape and Horizons, European Science Foundation, Strasbourg, http://archives.esf.org/fileadmin/Public_documents/Publications/moforum_research_careers.pdf.
ESF EUROAC (2015), “Career tracking of doctorate holders. Detailed reports”, in Fumasoli, T., G. Goastellec and M.B. Kehm (eds.), Academic Work and Careers in Europe: Trends, Challenges, Perspectives, Springer International Publishing, Basel.
European Commission (2015), She Figures 2015, Directorate-General for Research and Innovation, European Commission, Brussels, https://ec.europa.eu/research/swafs/pdf/pub_gender_equality/she_figures_2015-final.pdf.
European Commission (2014), The EURAXESS initiative: Mobilisation of research careers, European Commission, Brussels, http://ec.europa.eu/programmes/horizon2020/en/h2020-section/euraxess-initiative-mobilisation-research-careers.
European Parliament (2014), A new strategy for gender equality post 2015: Report to the Committee on Women's Rights and Gender Equality of the European Parliament, European Parliament Publications Office, Strasbourg, http://www.europarl.europa.eu/RegData/etudes/STUD/2014/509984/IPOL_STU(2014)509984_EN.pdf.
Heilman, M.E. (2012), “Gender stereotypes and workplace bias”, Research in Organizational Behavior, Vol. 32/0, pp. 113-135, https://doi.org/10.1016/j.riob.2012.11.003.
Hill, C., C. Corbett and A.S. Rose (2010), “Why so few? Women in Science, Engineering, Technology and Mathematics”, AAUW, Washington, DC, https://www.aauw.org/files/2013/02/Why-So-Few-Women-in-Science-Technology-Engineering-and-Mathematics.pdf.
Hinnant, C.C. et al. (2012), “Author-team diversity and the impact of scientific publications: Evidence from physics research at a national science lab”, Library & Information Science Research, Vol. 34/4, pp. 249-257, Elsevier, Amsterdam, https://doi.org/10.1016/j.lisr.2012.03.001.
Janger, J. et al. (2017), “MORE3 – Support Data Collection and Analysis Concerning Mobility Patterns and Career Paths of Researchers. Final Report – Task 4: Comparative and Policy-relevant Analysis”, WIFO Studies, No. 60891, Austrian Institute of Economic Research,Vienna, https://ideas.repec.org/b/wfo/wstudy/60981.html.
Jeppesen, L.B. and K. Lakhani (2010), “Marginality and problem solving effectiveness in broadcast search”, Organization Science, Vol. 21/5, pp. 1016-1033, HBS Scholarly Articles, Harvard Business School, Boston, MA, http://nrs.harvard.edu/urn-3:HUL.InstRepos:3351241.
Leslie, S.-J. et al. (2015), “Expectations of brilliance underlie gender distributions across academic disciplines”, Science, Vol. 347/6219, pp. 262-265, American Association for the Advancement of Science, Washington, DC, https://doi.org/10.1126/science.1261375.
Levanon, A., P. England and P. Allison (2009), “Occupational feminization and pay: Assessing causal dynamics using 1950-2000 U.S. Census data”, Social Forces, Vol. 88, pp. 865-892, Oxford University Press and University of North Carolina Press, Oxford and Chapel Hill, NC, https://doi.org/10.1353/sof.0.0264.
McKinsey (2015), The Power of Parity: How Advancing Women's Equality can add $12 trillion to Global Growth, McKinsey & Company, New York, www.mckinsey.com/featured-insights/employment-and-growth/how-advancing-womens-equality-can-add-12-trillion-to-global-growth.
Miller, D.I., A.H. Eagly and M.C. Linn (2015), “Women’s Representation in Science Predicts National Gender-Science Stereotypes: Evidence From 66 Nations”, Journal of Educational Psychology, Vol. 107/3, pp. 631-644, American Psychological Association, Washington, DC, https://doi.org/10.1037/edu0000005.
Miller, D.I. et al. (2018), “The Development of Children's Gender‐Science Stereotypes: A Meta‐analysis of 5 Decades of U.S. Draw‐A‐Scientist Studies”, Child Development, Vol. 0/0, Wiley and Society for Research in Child Development, Hoboken and Ann Arbor, https://doi.org/10.1111/cdev.13039.
Miller, D.I. and J. Wai (2015), “The bachelor’s to Ph.D. STEM pipeline no longer leaks more women than men: a 30-year analysis”, Frontiers in Psychology, Vol. 6/37, Frontiers Media, Lausanne, https://doi.org/10.3389/fpsyg.2015.00037.
MORRI (2015), Analytical report on the gender equality dimension, Monitoring the Evolution and Benefits of Responsible Research and Innovation (MoRRI), http://morri-project.eu/reports/2015-04-01-d2.3.
NSF (2017), Women minorities and persons with disabilities in science and engineering. Interactive dataset and report, National Science Foundation, Arlington, VA, https://www.nsf.gov/statistics/2017/nsf17310/digest/about-this-report/.
Nature Editorial (2005), “Separating Science from Stereotype”, Nature Neuroscience, Vol. 253/8, Nature Publishing Group, London, https://doi.org/10.1038/nn0305-253.
OECD (forthcoming), “Bridging the Digital Gender Divide: Include, Upskill, Innovate”, OECD Publishing, Paris.
OECD (2018a), Empowering women in the digital age: where do we stand?, High-level event
at the margin of the 62nd Session of the UN Commission on the Status of Women, 14 March 2018, New York City, OECD, Paris, https://www.oecd.org/social/empowering-women-in-the-digital-age-brochure.pdf.
OECD (2018b), OECD Main Science and Technology Indicators, www.oecd.org/sti/msti.htm (accessed on 18 June 2018).
OECD (2017a), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris, https://doi.org/10.1787/9789264281318-en.
OECD (2017b), EC/OECD STI Policy survey, OECD, Paris, https://stip.oecd.org/stip.html.
OECD (2017c), OECD Science, Technology and Industry Scoreboard 2017: The digital transformation, OECD Publishing, Paris, https://doi.org/10.1787/9789264268821-en.
OECD (2017d), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/eag-2017-en.
OECD (2009), Education at a Glance 2009: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/eag-2009-en.
OECD (2006), Women in Scientific Careers: Unleashing the Potential, OECD Publishing, Paris, https://doi.org/10.1787/9789264025387-en.
OECD/UNESCO (2017), OECD/UNESCO Institute for Statistics/Eurostat Careers of Doctorate Holders (CDH) project, OECD/UNESCO, Paris, http://oe.cd/cdh.
O'Neil, C. (2016), Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Crown Publishing, New York.
Peterson Institute for International Economics (2016), "Is Gender Diversity Profitable? Evidence from a Global Survey", Peterson Institute for International Economics Working Paper, Vol. 16/3, February 2016, Peterson Institute for International Economics, Washington, DC, https://piie.com/publications/working-papers/gender-diversity-profitable-evidence-global-survey.
Pollitzer, E. and M. Schraudner (2015), "Integrating Gender Dynamics into Innovation Ecosystems", Sociology and Anthropology, Vol. 3/11, pp. 617-626, Horizon Research Publishing Corporation, San Jose, CA, https://doi.org/10.13189/sa.2015.031106.
Saini, A. (2017), INFERIOR – How Science Got Women Wrong and the New Research That's Rewriting the Story, Beacon Press, Boston.
Smith-Doerr, L., S.N. Alegria and T. Sacco (2017), "How Diversity Matters in the US Science and Engineering Workforce: A Critical Review Considering Integration in Teams, Fields, and Organizational Contexts", Engaging Science, Society and Technology, Vol. 3/17, pp. 139-153, https://doi.org/10.17351/ests2017.142.
Vinkenburg, C.J. (2017), "Engaging Gatekeepers, Optimizing Decision Making, and Mitigating Bias: Design Specifications for Systemic Diversity Interventions", The Journal of Applied Behavioral Science, Vol. 53/2, pp. 212-234, Sage Journals, Thousand Oaks, CA, https://doi.org/10.1177/0021886317703292.
Williams, J. C., K.W. Phillips and E.V. Hall (2016), "Tools for change: Boosting the Retention of Women in the STEM Pipeline", Journal of Research in Gender Studies, No. 6/1, p. 11, Addleton Academic Publishers, New York, https://repository.uchastings.edu/faculty_scholarship/1434.
Notes
← 1. https://homewardboundprojects.com.au/
← 2. For instance, a comprehensive overview of the digital gender divide, including innovation-related aspects, can be found in “Bridging the Digital Gender Divide: Include, Upskill, Innovate” (OECD, forthcoming).
← 3. The Gender Gap Index was introduced by the World Economic Forum as an overall measure of gender inequality at the national level. See: https://www.wikigender.org/wiki/global-gender-gap).
← 4. https://www.inspiringthefuture.org/.
← 5. https://primaryfutures.org/.
← 6. See the 2018 report: https://www.educationandemployers.org/drawing-the-future/.
← 7. http://www.youngscientists.com.au/.
← 8. http://lettoysbetoys.org.uk/ten-ways-to-challenge-gender-stereotypes-in-the-classroom/.
← 9. https://girlswhocode.com/.
← 10. http://www.desy.de/schule/mint_fuer_maedchen/index_ger.html.
← 11. http://www.iop.org/publications/iop/2015/file_66429.pdf.
← 12. For the winning video, see: https://youtu.be/bDZF62gd1L4.
← 13. http://www.expecteverything.eu/hypatia/.
← 14. https://www.womeninc.nl/beperktzicht/.
← 15. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/imageofstemdepictiondoc_02102016_clean.pdf.
← 16. http://www.unstereotypealliance.org/en.
← 17. http://ec.europa.eu/eurostat/statistics-explained/index.php/Europe_2020_indicators_-_education.
← 18. https://cordis.europa.eu/project/rcn/105764_en.html.
← 19. Evelyne Sullerot (1924-2017) was a French feminist, philosopher and writer. Sullerot's Law states that if women become the majority in a certain vocation, then prestige and salary will be lower than if men are the majority.
← 20. http://wiseli.engr.wisc.edu/breakingbias_gender.php.
← 21. https://www.vr.se/english/calls-and-decisions/assessment-of-applications/gender-equality.html.
← 22. http://cerca.cat/en/women-in-science/bias-in-recruitment/.
← 23. https://erc.europa.eu/thematic-working-groups/working-group-gender-balance.