Realizing that the low representation of women in science and engineering is a major hindrance to global capacity building in science and technology, the IAC formed an Advisory Panel on Women for science with the mandate to review previous studies, provide examples of effective projects already implemented, and issue a set of actionable recommendations addressed particularly to the world’s science and engineering academies.
The recommendations and action items developed through the work of this Panel are presented in this report and are grouped around three themes:
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If organizations are to make progress not only in the number of women in science and technology but in their levels of achievement and influence, the Advisory Panel believes that the problems of stereotyping, isolation, and exclusion must be tackled.
In recognition of the importance of using human resources wisely, the European Commission, the United Nations, and many employers have introduced ‘good management practice’: consideration of the differential impact on women and men of all policies, programmes, and practices that the organization puts into place. This strategic approach goes well beyond ‘equal treatment,’ or making discrimination based on sex illegal. Equal treatment (gender neutrality) often works to the disadvantage of women by not taking into account the differences in employment characteristics of women and men. Good management practice also transcends ‘positive action,’ or the introduction of special measures to redress disadvantages that women have experienced.
Good management practice addresses inequalities by modifying the policies and procedures of an organization so that they are fair and open for all employees. In this way, all individuals—not only from both sexes but also from diverse ethnic backgrounds, as well as the disabled —are included, with the entire staff valued as talented contributors to the wellbeing and performance of the organization. Diversity, from this perspective, is embraced as a competitive advantage, providing the entity with a wider range of experiences and viewpoints. Sociological research (Rees, 1998; Etzkowitz et al., 2000; Glover, 2000), meanwhile, has provided an apt justification for changing a homogeneous institutional culture to one that is welcoming and inclusive of a diverse staff. Diversity is observed not only to be fair but also far better at achieving the organization’s practical goals. The basic principles of good management practice are summarized in Box 2.1.
Good management practice implies the organization ’s commitment to equal pay for equal work; to including women and minorities in top management positions; and to offering provisions such as flexible working hours, telecommuting, and on-site childcare for employees, female and male alike, who are raising children. An example of good management practice in industry is given in Box 2.2.
Good management practice requires changing an organizational culture. This requires mundane efforts such as setting benchmarks and monitoring progress based on sex-disaggregated data. But many organizations do not routinely collect such data. Even when available, the comparison of data on national or international scales is difficult. For instance, the specific fields included among science disciplines, as opposed to engineering disciplines, vary from university to university and from country to country. Following a specified and uniform format, such as that put in place by the European Union (European Commission, 2003), would be a big step forward in measuring women’s progress.
The UNCSTD Gender Advisory Board recently produced a toolkit for gender indicators in science and technology to facilitate the collection and comparison of gender-disaggregated data (UNCSTD/GAB, 2003). A similar toolkit, called WinSETS (Women in Science and Technology Scoreboards), was developed at Stellenbosch University in the Republic of South Africa (Bailey and Mouton, 2004). Both of them permit easy comparison of gender indicators across disciplines and between countries (Table 2.3).
Many of the programs and policies for the improvement of women’s status in science and technology, such as they are, were put into place only recently. Likewise the collection of disaggregated data in science and technology is also quite new. And with data-reporting usually lagging one or more years, the kind of long-range solid evidence that academies would love to see is simply unavailable. But if that is used as justification not to start making change, a vicious circle will be created, ensuring that the evidence will not be available in the future either.