Eine interessante Studie bespricht eine Vielzahl von Gründen, warum sich Geschlechterunterschiede im STEM-Bereich ergeben.
It is a well-known and widely lamented fact that men outnumber women in a number of fields in STEM (science, technology, engineering and maths). The most commonly discussed explanations for the gender gaps are discrimination and socialization, and the most common policy prescriptions target those ostensible causes. However, a great deal of evidence in the behavioural sciences suggests that discrimination and socialization are only part of the story. The purpose of this paper is to highlight other aspects of the story: aspects that are commonly overlooked or downplayed. More precisely, the paper has two main aims. The first is to examine the evidence that factors other than workplace discrimination contribute to the gender gaps in STEM. These include relatively large average sex differences in career and lifestyle preferences, and relatively small average differences in cognitive aptitudes – some favouring males, others favouring females – which are associated with progressively larger differences the further above the average one looks. The second aim is to examine the evidence suggesting that these sex differences are not purely a product of social factors but also have a substantial biological (i.e. inherited) component. A more complete picture of the causes of the unequal sex ratios in STEM may productively inform policy discussions.
Die Einteilung in der Studie ist wie folgt:
- Sex differences in preferences and priorities
- Sex differences in cognitive aptitudes
- Sex differences in variability
- Bias and discrimination in the workplace
- Policy implications
- Levelling the playing field vs. equalizing sex ratios
- Conclusion: Many factors at play
Ich dachte ich gehe diese Punkte mal einzeln durch, weil da viel interessantes dabei ist
Los geht es:
Sex differences in STEM representation are not just an academic matter. The question of what should be done about these differences – or indeed whether anything should be done – is one of the most widely discussed political issues related to the modern academy. Various interventions have been suggested and implemented over the years, including bolstering key skills in early life or in college, signalling a commitment to diversity in the workplace, and providing same-sex mentors and role models for women (Cheryan et al., 2017; Dasgupta & Stout, 2014; Diekman et al., 2015; Uttal et al., 2013; Walton et al., 2015; for a comprehensive list of policy options, see Williams et al., 2017). The literature on this issue is voluminous and beyond the scope of this article. What we aim to do in this section, however, is outline some of the ways in which the ideas discussed thus far may contribute to the discussion of policy options. One thing to make clear at the outset is that these ideas do not imply that we should do nothing or that nothing we do will work. Although our analysis may undermine some arguments for some policies, it may bolster the case for others and suggest novel avenues for intervention as well.
Also die Frage was man (evtl.) machen könnte oder nicht machen könnte bzw welche politischen Auswirkungen die zuvor besprochenen Punkte haben.
OutreachAn initial, relatively uncontroversial intervention is outreach: educating children and young people about STEM-related careers, and emphasizing that these are careers that females as well as males should consider (Vennix et al., 2018; J. R. Young et al., 2017). This can be done overtly or by including female STEM professionals among those providing the outreach (Dasgupta & Stout, 2014).11 Advocates of such interventions would not need to deny that there are average differences between the sexes in STEM-relevant traits. On the contrary, average sex differences provide an argument in favour of the intervention. After all, even if gender gaps in STEM representation are primarily a result of sex differences in preferences, aptitudes and variability, the mere existence of these gaps could still help sway the career choices of individuals whose interests and talents buck the usual trend. Some girls and women who would otherwise pursue a STEM career might be put off by the fact that more men than women take that path, at least in fields where the gap is especially large (Dasgupta & Stout, 2014). That being the case, it might always be necessary to encourage and support these individuals, and to encourage everyone else to accept atypical career choices and be tolerant of individual differences. (Notice, incidentally, that the same argument would weigh just as heavily towards encouraging boys and men with atypical career preferences to follow their interests too – something far less often discussed.)An understanding of average sex differences could also help educators pitch STEM to girls and women. As mentioned, part of the reason that fewer girls and women are interested in a career in STEM (or rather a career in a certain subset of STEM fields) may be widespread stereotypes about what that career would entail. These include such stereotypes as that STEM careers offer few opportunities to pursue communal goals (e.g. working with and helping other people), that STEM careers involve social isolation and a strong focus on mechanisms and materials, and that STEM workplaces are sexist and unwelcoming of women (Cheryan et al., 2015; Diekman et al., 2017).
Also die Frauen, die in den Bereichen gut abschneiden und dafür Interesse haben dazu überreden auch in diesem Bereich zu arbeiten und gerade die feministische Propaganda zurückfahren, dass dort alles voller Sexismus ist und Frauen deswegen das nicht machen wollen.
Es wäre interessant, wie eine Werbung für die Bereiche aussehen würde, die statt „Hört endlich mit dem Sexismus aus Männer, dann kommen auch die Frauen“ oder “ es gibt keine Unterschiede zwischen den Geschlechtern, nur Sexismus“ auf weibliche Vorlieben abstellt und ob das möglich ist. Wäre interessant, wie man die Arbeit an technischen Sachen als Arbeit mit Menschen verkaufen kann. Man wird zB als Lehrerin immer mehr mit Menschen zu tun haben als als tatsächlicher Ingenieur. Würde eine Werbung „Informatik ist der perfekte Beruf für Frauen, weil man als Informatiker immer auch von zuhause arbeiten kann und das gut mit der Kinderbetreuung vereinbar ist“ ziehen? Und wie würden Feministen wohl darauf reagieren?
One way to encourage more girls and women to consider a career in a male-dominated STEM field, then, may be to challenge these common stereotypes (Cheryan et al., 2015). (Needless to say, this should be done only to the extent that the stereotypes in question are in fact inaccurate.)Of course, as with any intervention, outreach has the potential to cause harm as well as good. One possible harm could come from programmes that focus only on girls: girls-only STEM workshops, for instance, or advertising campaigns that depict girls but not boys engaged in STEM-related activities (see, e.g. Mervis, 2018). Such programmes could inadvertently convey the message to boys that they are no longer welcome in STEM, and that if they choose to pursue a career in that area, they may face an uphill battle due to institutional favouritism towards girls and women.
Hehe. Bevorzugung von Frauen als etwas schlechtes?
This is a speculation, certainly, but one consistent with common arguments about the factors that can turn girls away from a career in STEM (Thoman & Sansone, 2016). Girls-only programmes could also risk losing the support of people who would otherwise be allies, but who worry that the issue has been captured by a strain of gender politics more concerned about eliminating sex differences than about opening the doors for all (Mervis, 2018).Another potential harm is that well-meaning efforts to encourage girls to pursue careers in STEM could sometimes tip over into excessive pressure to take that path. Susan Pinker (2008) interviewed women who had left successful STEM careers to pursue careers in other areas. Many reported that, as girls and young adults, they were so strongly encouraged to go into STEM that they ended up in jobs they did not especially enjoy. Granted, this is only one of many reasons that women give for leaving STEM (Glass et al., 2013). Still, in light of this potential pitfall, we suggest that the aim of outreach should not be to get women into STEM per se, but rather to give everyone accurate information about STEM career options so that they can make an informed choice about what would suit them best. (For evidence that having a job that matches one’s interests and skills predicts job satisfaction, see, e.g. Bretz & Judge, 1994; De Fruyt, 2002; Verquer et al., 2003.)
Erfrischend, dass angesprochen wird, dass eine zu starke Kampfrhetorik schlicht eine Gegenbewegung erzeugen kann, die es dann schwieriger und nicht einfacher macht. Und auch ein interessanter Ansatz, dass viele, denen zu viel versprochen worden ist, dann wieder in ganz andere Bereiche gehen, weil es ihnen letztendlich nicht gefällt.
Es gibt eben immer Ausweichmöglichkeiten, etwa als Journalistin über Themen aus dem Bereich zu berichten.
Incentives for women to go into STEMA second broad class of interventions involves offering incentives for women to go into male-dominated STEM fields. Examples include female-only scholarships, fee waivers and monetary incentives for completing one’s training in a targeted area. As with outreach, this is already a common practice, and it seems probable that the incentives on offer would encourage more women to make gender-atypical choices (Navarra-Madsen et al., 2010).But although the incentives probably work, a number of arguments can be levelled against the practice. One is that it discriminates on the basis of sex: it offers advantages and opportunities to some individuals but not others, purely on the basis of a fixed biological attribute. Even leaving this aside, however, it is worth considering the wisdom of devoting large amounts of resources to encouraging women to do something they would not otherwise do. Although rarely described that way, this is clearly what the practice amounts to; after all, if the targeted women did want to do it anyway, the incentives would not be necessary. By interfering with women’s choices, it is possible that immediate incentives could nudge some women away from options that might suit them better in the longer term and which might ultimately make them happier (Bretz & Judge, 1994; De Fruyt, 2002; Verquer et al., 2003).12 Of course, people are not always right about what will make them happy. It seems unlikely, however, that the incentives under discussion would increase people’s chances of getting it right – especially given that the aim of these incentives is not to raise people’s happiness but rather to minimize sex differences.
Auch sehr erfrischend in seiner Klarheit:
Förderprogramme nur für Frauen sind zum einen Sexismus und zum anderen versuchen sie Frauen in Bereiche zu bringen, in die sie vielleicht sonst nicht gegangen wären, was dafür sprechen kann, dass sie da nicht wirklich hinwollen.
Dagegen könnte sprechen, dass man, wenn man in einem Bereich angekommen ist, diesen ja durchaus schätzen gelernt haben kann.
Das Argument, dass es den Initiatoren allerdings nicht darauf ankommt, dass das Individuum glücklicher ist, sondern es eher darum geht, dass es eben bestimmte Frauen für die Gruppe der Frauen machen müssen, ist aber durchaus interessant.
Gender-blind evaluationA third intervention is gender-blind evaluation of job applications, journal article submissions, grant applications and the like – that is, removing any evidence of the applicant or author’s sex before beginning the evaluation process (Jones & Urban, 2013). Where this can be done, it is a relatively easy way to neutralize the potentially distorting effects of demographic stereotypes. A possible criticism of the practice, at least as applied to hiring decisions, is that it could only be implemented during the earliest stages of the hiring process: gender can be largely concealed in a CV, but not in an interview or job talk. Against such concerns, however, a great deal of research suggests that stereotypes exert most of their influence on person perception during those earliest stages, when perceivers have little individuating information about the person being perceived (Koch et al., 2015; Rubinstein et al., 2018). As such, blind evaluation could well eliminate most of the biasing effects of demographic stereotypes. Another advantage of blind evaluation is that it automatically eliminates all forms of bias, including not only anti-female bias but anti-male bias too. Moreover, if there is little bias in either direction, gender-blind evaluation would simply have no effect. In other words, the procedure automatically calibrates the size of its impact to the level of gender bias, unlike most anti-bias strategies.Despite its merits, gender-blind evaluation may prove to be a politically unpopular option. If Ceci and Williams (2011; Williams & Ceci, 2015) are right that women are often favoured rather than disfavoured in STEM hiring, blind evaluation of job applications would presumably result in somewhat fewer women being hired than is presently the case. Given the strong push towards increasing the numbers of women in STEM, such an outcome is likely to rule against the policy. This is not mere speculation; the Australian Public Services recently suspended a blind-evaluation trial when they discovered that the practice slightly increased men’s chances of getting hired, and slightly decreased women’s (Hiscox et al., 2017). Notice that, in abandoning the trial, the policy makers effectively revealed that their goal is equality of outcome rather than equality of opportunity – a key distinction we return to soon.
„Blinde Einstellungsauswahl“ wäre also ein interessantes Mittel, könnte aber im STEM-Bereich den Nachteil haben, dass dann eben weniger Frauen eingestellt werden. Eben weil momentan Frauen gesucht werden und damit auch genommen werden, wenn Männer eigentlich besser qualifiziert sind. Interessant der Fall aus Australien, die genau diese Erfahrung gemacht haben.
Anti-bias trainingAnother intervention aimed at weeding out discrimination in STEM is diversity training, also known as anti-bias training. This intervention takes many forms, but the common thread is the aim of increasing awareness and tolerance of diversity in the workplace, and helping people from different backgrounds to avoid bias and to work together harmoniously. The practice has become increasingly popular over the last half-century, and is now a billion-dollar industry (Hansen, 2003).In spite of its laudable aims and popularity, though, a number of criticisms and concerns have been raised about anti-bias training. For present purposes, the most important is that, in its application to STEM gender gaps, the entire enterprise is premised on the assumption that bias is the primary cause – or at least a major cause – of the differential representation of men and women in STEM. As we saw earlier, however, the evidence for endemic anti-female bias is inconclusive at best, and the main cause of the gender gaps in STEM appears to be average sex differences in people’s vocational preferences. This raises serious questions about the utility of anti-bias training. If bias is no longer the main driver of STEM gender gaps, then interventions targeting bias are likely to have little positive impact. And if that’s the case, then anti-bias training represents a considerable waste of resources: resources that could otherwise be channelled into interventions more likely to achieve their aims.
Anit-Bias Training beruht auf dem Gedanken, dass Bias bzw Vorurteile das Problem sind. Wenn das nicht der Fall ist bzw nicht bewiesen werden kann, dann bringen diese Programme wenig (noch weniger, wenn sie als Angriff verstanden werden, weil man zB Männer abwertet)
Consistent with this assessment, research on the efficacy of anti-bias training paints a decidedly mixed picture. Various studies have concluded that the most popular programmes and policies have little impact on diversity outcomes (Bradley et al., 2018; Chang et al., 2019; Kalev et al., 2006). More than that, in some cases, anti-bias interventions may backfire, increasing rather than reducing bias (Duguid & Thomas-Hunt, 2015; Moss-Racusin et al., 2014; Vorauer, 2012).The concept of implicit or unconscious bias has been a particular focus of critical attention in recent years. Several studies have concluded that tests of implicit bias (in particular, the Implicit Association Test or IAT) have poor test–retest reliability (Gawronski et al., 2017), and fail to predict discriminatory behaviour (Cameron et al., 2012; Greenwald et al., 2009; Oswald et al., 2015). Furthermore, though interventions may change people’s implicit biases to some degree – or do so, at least, in the short-term – the effects of such changes on behaviour are trivially small or non-existent, even in the immediate wake of the intervention (Forscher, Lai, et al., 2019). For all these reasons, it seems unlikely that interventions targeting implicit bias represent a wise allocation of resources.Of course, it is possible in principle that anti-female bias is still pervasive in STEM but that we have yet to find effective interventions to tackle it. In light of our earlier discussion, however, it seems more likely that anti-bias interventions are simply not targeting the main causes of women’s lower representation in STEM.
Eine schöne Breitseite gegen das Anti-Bias Training und damit gegen Personen wie Robin DiAngelo und den Rest der Beratungsindustrie. Ich merke mir diesen Absatz mal für eine weitere Besprechung vor.
Preferences and quotasAnother strategy for shrinking STEM gender gaps would be to establish preferences for women in male-dominated fields. Sometimes known as positive discrimination or affirmative action, this approach would include everything from giving preference to women from among similarly qualified candidates, to earmarking jobs for women only, to establishing strict quotas for women in STEM in terms of hiring, promotion or grant funding. To some extent, such policies exist already, both formally (Baker, 2019; Boisvert & Hancock, 2018; Dance, 2019; Davey, 2016; Matthews, 2017) and informally (Ceci, 2018; Williams & Ceci, 2015). Some argue, however, that the policies should be rolled out more widely in the effort to combat STEM gender gaps (Crosby et al., 2003; Wallon et al., 2015). Among the most common arguments for this position are that preferences would provide a counterweight to existing discrimination, compensate for the lingering effects of past discrimination, hasten the pace of scientific progress by increasing viewpoint diversity, enlarge the pool of same-sex role models and mentors for girls and women and break the cultural ‘habit’ of male-dominance in certain STEM fields in a way that more laissez-faire approaches so far have not (Fullinwider, 2018).
Also das Argument, dass Quoten:
- Ein Gegengewicht gegen den bremsenden Effekt der Diskriminierung bewirken und diese damit lediglich ausgleichen
- Die immer noch bestehenden Effekte früherer Diskriminierung ausgleichen
- Eine Beschleunigung des Fortganges der Wissenschaft bewirken, in dem andere Standpunkte einfließen
- Vorbilder und Mentoren schaffen
- Die Dominanz der Männer in diesen Bereichen durchbrechen.
Perhaps unsurprisingly, preferences and quotas seem to increase the representation of targeted groups in areas where these policies are utilized (Kurtulus, 2016; Wallon et al., 2015). Nonetheless, as with other policy options, various concerns have been raised regarding the practice, especially in its more heavy-handed forms. The first is a question of ethics. Pro-female favouritism represents an explicit rejection of the principle of equality of opportunity in favour of discrimination on the basis of sex: precisely what feminism originally set out to overcome. As the philosopher Janet Radcliffe-Richards (2014) argued, one of the main moral foundations of the women’s liberation movement – and indeed of all liberation movements – is the idea that individuals should be treated fairly and equally, and that unjust barriers should be removed. A policy that advantages members of one demographic group over those of another necessarily abandons those principles. In doing so, it risks leaving the women’s movement without one of its main moral foundations.
Wenn man Chancengleichheit durch Ergebnisgleichheit ersetzt, dann verliert man als Antidiskriminierungsbewegung seine moralische Grundlage.
Dann hat der Feminismus diese Grundlage bereits lange verloren. Allerdings würde man dort einwenden, dass gleiche Chancen ja dazu führen müssen, dass es auch ein gleiches Ergebnis ergibt, weil Männer und Frauen gleich sind und nur ihre sozialen Rollen abweichen. Von da an würde man sich wieder in eine Diskussion über soziale und biologische Ursachen oder aber den Umstand, dass Karriere keineswegs alles ist und andere Faktoren zurecht in einer Gruppe populärer sein können stürzen müssen.
One response to this argument might be to point out that, throughout history, men were often advantaged over women in exactly this kind of way. As a stand-alone argument, however, this seems unpersuasive. Why should any individual woman today be advantaged over any individual man just because other men were advantaged over other women in the past? Reversing historical injustices does not erase them; it merely adds to the total number of injustices in the world. The question we face today, therefore, is this: is the appropriate response to injustice to try to eliminate it, or to turn it on its head?Of course, some would argue that preferences and quotas for women in STEM would not in fact be unjust; on the contrary, they would help to equalize men and women’s chances of advancing in STEM, which are currently unequal due to present-day anti-female discrimination or the persisting effects of anti-female discrimination in the past (Crosby et al., 2003; Radcliffe-Richards, 2014; Walton et al., 2013). As discussed, however, the evidence for pervasive present-day discrimination in STEM is equivocal, with some studies suggesting that, at least in certain ways, women are favoured over men (Williams & Ceci, 2015). Moreover, though it is certainly possible that current STEM gender gaps are partly a cultural holdover from past discrimination, we are unaware of any rigorous attempt to demonstrate or measure this, or to weigh the effects of past discrimination against the countervailing effects of contemporary efforts to attract more women into STEM. Given that advantaging one demographic group over another is not an ethically trivial act, we should be circumspect about adopting such a policy on the basis of conflicting and contested evidence – especially given that other policy options are available.
Ein schöner Absatz. Man kann nicht beweisen, dass es tatsächlich überbleibsel einer Diskriminierung sind oder eine Diskriminierung anhält, also ist keine Grundlage dafür vorhanden, dass man die Rechte anderer so stark einschränkt.
Furthermore, it is not only men who may be harmed by preferences and quotas. In a number of ways, women could be harmed as well. To begin with, such policies could cast a shadow of doubt over women’s genuine accomplishments (Heilman et al., 1992, 1997). If the policies become widespread, then whenever women win jobs, grants or awards, people might find themselves wondering – secretly and despite their best intentions – whether the women in question were judged by a lower standard, simply because of their sex (a rather sexist practice in itself, one might argue). This is not only a pitfall for onlookers; successful women themselves could end up harbouring doubts about their own achievements (Unzueta et al., 2010; although see M. C. Taylor, 1994).As well as casting doubt on the success of individual women, preferences and quotas could harm the image of women in STEM more generally.
Letztendlich das Dilemma der Quotenfrau. Wenn sie als eine solche angesehen wird, dann ist das – auch wenn es in Deutschland Kampagnen gab, die Quotenfrau positiv zu framen – eine schlechte Eigenschaft. Es führt zu der Unsicherheit ob sie es aufgrund ihrer Qualifikation geschafft hat oder aufgrund der Quote.
One of the primary goals of the women-in-STEM movement has been to eliminate the pernicious and demonstrably false stereotype that women cannot succeed in STEM. Preferences and quotas are unlikely to contribute to that project. On the contrary, the policies could bolster the stereotype. Aside from the fact that they might seem to imply that women need the extra help, strong preferences could lower the average level of performance of women working in STEM (cf. Haidt & Jussim, 2016). This is not because any individual woman would perform any worse, but rather is a simple statistical consequence of the fact that the pool of female STEM candidates is smaller than that of the males. As shown in Figure 4, if equal numbers of top performers are taken from two samples, but one of those samples is smaller than the other, then – all else being equal – the mean level of ability of those from the smaller sample will be lower than that from the larger, even if the means and variances of the two samples are identical. In effect, equalizing the number of individuals taken from each group would mean lowering the minimum standard for the smaller group.Figure 4. If equal or similar numbers of top performers are drawn from samples of different sizes (represented here by the shaded areas of the two distributions), the average level of ability of those drawn from the smaller sample will be lower than that of those drawn from the larger. This is the case even if the means and variances of the two groups are identical.This could have damaging consequences for women. In the absence of preferences or quotas, a person’s sex tells you little about their probable STEM abilities: any woman who has been accepted to a given university, or secured a job at a given institution, is likely to be just as talented as any man at the same university or at the same institution. However, if strong preferences or quotas are put in place, sex suddenly does tell you something about women’s probable STEM abilities: it tells you that they might not necessarily be as good (cf. Haidt & Jussim, 2016). Again, this is not because women cannot succeed in STEM – some can and some cannot, just like men. Instead, it is a predictable consequence of the fact that enacting strong preferences for members of a smaller group generally means lowering the minimum standard by which members of that group are judged.
Frauenquoten müssen fast zwangsläufig dazu führen, dass die Qualität der Kandidatinnen im Schnitt sinkt. Einfach weil der Pool der Frauen, die verfügbar sind, kleiner ist als der Pool der Männer und es keine Anzeichen dafür gibt, dass innerhalb dieses Pools dann eine höhere prozentuale Anzahl an sehr guten Kandidaten ist.
Dagegen könnte man einwenden, dass ja bei den Frauen alle weniger guten verschreckt werden, weswegen bereits eine Bestenauslese in dem Pool enthalten ist. Aber das ist recht wenig überzeugend.
Family-friendly policiesA final proposal is that STEM career paths could be reconfigured in ways that would make them more family-friendly (Mason et al., 2013). This is a view that Ceci and Williams (2010, 2011; Williams & Ceci, 2012) have championed. In their estimation, one of the main remaining barriers to career success for women in STEM is the incompatibility of jobs in this area with the demands of motherhood. Not only do women alone get pregnant and nurse their young, but women are more likely than men to take time out from their careers to care for their children, and more likely to leave STEM altogether after first becoming parents (Cech & Blair-Loy, 2019). Of course, to some extent, this may reflect evolved differences in men and women’s motivations, rather than just norms and social pressure (Stewart-Williams, 2018), and we are not suggesting that women are necessarily wrong to make these choices. However, the structure of STEM may sometimes create tensions between women’s careers and motherhood that are unnecessary and that could potentially be eliminated.Nowhere is the clash between STEM and motherhood more apparent than with regard to the academic tenure system in the United States and Canada. As Ceci and Williams (2010) put it:The tenure structure in academe demands that women having children make their greatest intellectual contributions contemporaneously with their greatest physical and emotional achievements, a feat not expected of men. When women opt out of full-time careers to have and rear children, this is a choice – constrained by biology – that men are not required to make. (p. 278)It is worth noting that the family-friendliness of STEM jobs varies a great deal from nation to nation, and that the US typically has less family-friendly policies than Europe and other Western regions. It is also worth noting that a lack of family-friendly policies would not explain why women are less well represented in maths-intensive fields than in most others. Nonetheless, finding ways to make STEM occupations more compatible with motherhood could help to level the playing field in maths-intensive and non-maths-intensive fields alike. Suitable policies might include providing paid leave for having or adopting children, increasing the provision of subsidized or on-campus childcare, instructing hiring and promotion committees to ignore family-related gaps in parents’ CVs and increasing the flexibility of the window in which academics are able to complete the requirements of tenure (Williams & Ceci, 2012; Williams et al., 2017).Of course, some might take issue with the ‘assumption’ that women are the primary caregivers for their young. But this is not an assumption in any normative sense; it is simply an observation about what tends to happen. And given that it is what tends to happen, and that the tendency may be rooted in psychological sex differences that are partly inherited and thus difficult to change (even assuming it would be ethically permissible to try to change other people’s preferences), family-friendly policies might help to equalize men and women’s opportunities by removing a barrier that faces more women than men. Furthermore, if enacted in a gender neutral way, such that mothers or fathers could avail themselves of any parental benefits, the policies would not exert any special pressure on women to take the primary caregiver role. Either sex could take it, if they so desired.13
Da wäre es interessant die Maßnahmen in den einzelnen Ländern zu vergleichen, denn es gibt ja bereits etwa in Deutschland Elternzeit etc. Es wäre interessant, welche Faktoren da zu einem höheren Anteil in STEM-Bereichen führen. Ich vermute der Effekt ist nicht sehr hoch. Eher wird jemand, der plant Elternzeit zu nehmen und danach in Teilzeit zu arbeiten, eher einen Beruf suchen, der ihm dies nach Möglichkeit erlaubt und da schneidet zB Lehrerin etc häufig besser ab als viele STEM-Bereiche. Natürlich kann man aber auch als Ingeneurin in einer großen Firma arbeiten, wobei man gerade in technischen Bereichen auch schneller ins Hintertreffen gerät, wenn man längere Zeit aussetzt und etwa die Arbeit an größeren Projekten oft einen erheblichen Zeiteinsatz erfordern kann. Ich kenne allerdings auch Frauen in technischen Berufen, die das gerade jetzt in Covid sehr gut mit Heimarbeit kombinieren können, solange sie die passende zB Planungssoftware auf dem Computer haben.