Eine interessante Studie zur Diskriminierung bei Einstellungen, die zu unerwarteten Ergebnissen kommt:
Abstract
Gender discrimination is often regarded as an important driver of women’s disadvantage in the labour market, yet earlier studies show mixed results. However, because different studies employ different research designs, the estimates of discrimination cannot be compared across countries. By utilizing data from the first harmonized comparative field experiment on gender discrimination in hiring in six countries, we can directly compare employers’ callbacks to fictitious male and female applicants. The countries included vary in a number of key institutional, economic, and cultural dimensions, yet we found no sign of discrimination against women. This cross-national finding constitutes an important and robust piece of evidence. Second, we found discrimination against men in Germany, the Netherlands, Spain, and the UK, and no discrimination against men in Norway and the United States. However, in the pooled data the gender gradient hardly differs across countries. Our findings suggest that although employers operate in quite different institutional contexts, they regard female applicants as more suitable for jobs in female-dominated occupations, ceteris paribus, while we find no evidence that they regard male applicants as more suitable anywhere.
Quelle: Gender Discrimination in Hiring: Evidence from a Cross-National Harmonized Field Experiment
Also ein groß angelegte Studie, die dennoch keine Diskriminierung gegen Frauen feststellen kann, allerdings eine Diskriminierung von Männern in Deutschland, den Niederlanden, Spanien und in der UK. Insbesondere werden wohl Frauen in überwiegend von Frauen dominierten Beschäftigungen als eher geeignet für den jeweiligen Beruf angesehen. Bei männlichen Bewerbern ist dies hingegen in keinem Bereich der Fall.
Zu der vorgefundenen Studien:
Some experiments found advantages for men over women (Neumark, Bank and Van Nort, 1996; Petit, 2007; Zhou, Zhang and Song, 2013; Duguet, Loïc and Petit, 2017; González, Cortina and Rodríguez, 2019), whereas other experiments found advantages for women over men (Jackson, 2009; Carlsson, 2011; Carlsson and Eriksson, 2017). Some studies found hiring discrimination against both men and women, depending on parental status (Correll, Benard and Paik, 2007) or gender composition and type of job (Weichselbaumer, 2004; Yavorsky, 2019), while other studies found no gender discrimination at all (Albert, Escot and Fernández-Cornejo, 2011; Capéan et al., 2012; Carlsson et al., 2014; Carlsson and Erikson, 2017; Bygren, Erlandsson and Gähler, 2017). Some studies found evidence of hiring discrimination against women in high-level jobs (Riach and Rich, 2002; Baert, De Pauw and Deschacht, 2016), while others did not (Williams and Ceci, 2015). These inconsistencies in findings might reflect true cross-national differences in gender discrimination. If institutional contexts, such as labour market policies, affect employers’ hiring decisions, they might, all else equal, behave differently in different national contexts (Gangl and Ziefle, 2009). However, as these experiments are adapted to national contexts, and the included occupations vary considerably, inconsistencies in findings might also be an artefact of heterogeneity of research designs.
Also eine Vielzahl von Studien, alle mit anderen Ansätzen. Diese Studie hier will nunmehr mit einem gleichen Ansatz in verschiedenen Ländern einen umfassenderen Ansatz verfolgen.
Noch zur weiteren Ausgangslage:
More consistently across contexts, field experiments on gender discrimination show that men are discriminated when they apply for female occupations, and women when they apply for male occupations (Riach and Rich, 2002, 2006; Booth and Leigh, 2010; Carlsson, 2011; Rich, 2014). ‘However, discrimination against men in “female” occupations was always much higher than that against women in “male” occupations’ (Riach and Rich, 2002: pp. F504–505). One study also found discrimination of men in female-dominated occupations, and no gender differences in hiring in mixed or male-dominated occupations (Ahmed, Granberg and Khanna, 2021). Thus, despite the obvious temptation, we cannot directly compare field-experimental evidence on gender discrimination across countries, due to heterogeneity in research designs across countries and time-periods.
To address this limitation, we make use of a harmonized cross-national field experiment in six countries: Germany, the Netherlands, Norway, Spain, the United Kingdom, and the United States [The Growth, Equal Opportunities, Migration and Markets (GEMM) study, conducted by Lancee et al., 2019b].1 To our knowledge, the GEMM study is the first randomized field experiment with a deliberate cross-national comparative design (Di Stasio and Lancee, 2019). These data allow us to provide new and rigorous evidence on gender discrimination in the first phase of the hiring process in six occupations in six countries. We contribute to the literature by analysing hiring discrimination within and across countries with different institutional characteristics.
Also eine doch etwas abweichende Studienlage als es sich der typische Feminist vorstellt. Eine Diskriminierung von Männern kommt in deren Denkweise ja gar nicht vor bzw ist bereits undenkbar.
Gender Discrimination: Theoretical Considerations
Hiring new employees always involves an element of risk-taking, as employers cannot know beforehand how an individual will perform. Employers rely on the information available in the cover letter and CV but may still be uncertain about the applicants’ skills. If employers believe members of a particular group are more productive than others, they might regard group membership as an informative cue. Obviously, employers’ expectations might be wrong, as they may rely on unfounded stereotypes about certain groups. In addition, even if employers’ beliefs are correct in terms of average group-level characteristics, individual job applicants may deviate substantially from a given group characteristic.2
In der Tat sind typische Geschlechterunterschiede erst einmal eine zusätzliche Informationsquelle, die aber nur mit einer gewissen Wahrscheinlichkeit zutreffend sind. Die Wahrscheinlichkeit lässt sich wahrscheinlich noch erhöhen, wenn man die „Weiblichkeit“ oder „Männlichkeit“ einer jeweiligen Person einschätzt. Aber selbst dann kann es natürlich sein, dass dennoch die gewünschte Eigenschaft, die im Schnitt der Gruppe eher vorliegt, bei der konkreten Person nicht stark erhöht ist.
Discrimination against Women
Several perspectives explain why employers discriminate against women. We have grouped the relevant theoretical approaches into two broader categories: (i) cultural perspectives focusing on social norms and gender stereotypes, and (ii) the economic-rational perspective addressing statistical discrimination.
According to cultural perspectives, employers rely on gender stereotypes and gender-differentiated work expectations. In Joan Acker’s seminal work on gendered organizations, gender inequality is an inbuilt characteristic of work organizations (Acker, 1990; Rudman and Phelan, 2008; Williams, Muller and Kilanski, 2012). Of particular importance is the norm of the ‘ideal worker’, working full-time without family obligations. As women’s work traditionally has been confined to the domestic sphere, this norm would disadvantage women in hiring situations (Acker, 1990). Even in large, modern organizations, there is evidence that women are held to other standards than men, which might explain the persistence of the glass ceiling in career promotion. The so-called ‘paradox of meritocracy’ (Castilla and Benard, 2010) implies that top-down directives oriented towards fairness and efficiency seem incapable of neutralizing discriminatory gender attitudes and may even reinforce the adverse effects of unconscious bias. Thus, despite societal trends towards gender convergence, theories about gendered organizations lead us to expect that men have an advantage over women in virtually all hiring processes.
The theory of statistical discrimination builds on the assumption that employers engage in cost-benefit calculations (Arrow, 1972; Phelps, 1972). This economic-rational perspective leads us to expect that employers assess the potential productivity of job applicants by their observable characteristics, such as human capital, and attribute average group characteristics to them to assess their unobservable characteristics (Fang and Moro, 2011). Due to productivity gains and because hiring in itself is costly, employers can be expected to be looking for stable workers. Given that women are more likely to be absent due to family responsibilities, employers would assess men’s productivity higher and discriminate against women, all else equal.
To summarize, both cultural and economic-rational perspectives lead us to expect discrimination of female applicants, primarily due to employers’ beliefs about women’s higher level of absence associated with childcare.
Also die klassischen Punkte: Frauen fallen mit einer höheren Wahrscheinlichkeit für einen gewissen Teil der Arbeitszeit aus und es ist für viele Arbeitgeber daher günstiger Männer anzustellen.
Discrimination against Men and Women
As noted above, previous experiments show differential gender discrimination across male- and female-dominated occupations. The cultural perspectives might explain why. Psychologists have developed the stereotype content model, which proposes that people tend to perceive men as competent but not warm, and women as warm but not competent (Glick and Fiske, 1996). People also perceive male-dominated jobs as requiring more competence and female-dominated jobs as requiring more warmth (Cuddy, Fiske and Glick, 2008). As these stereotypes are associated both with individuals and jobs, it is highly plausible that employers discriminate applicants with the ‘wrong’ gender (Bobbitt-Zeher, 2011). Thus, ‘if a caregiving job is thought to require warmth and men are thought to not possess much warmth, individuals may expect that a man will not be successful at a caregiving job’ (Halper, Cowgill and Rios, 2019: p. 2). By the same logic, employers would form negative performance expectations of women in—for instance—technical jobs. Thus, employers’ gender stereotypes might steer the process of matching jobs and job applicants. Theoretically, this argument is captured by the concept of sex typing of jobs (Bielby and Baron, 1986; Glick, Zion and Nelson, 1988; Reskin and Roos, 1990), the role congruency model (Cejka and Eagly, 1999), and the theory of gender categorization within work organizations (Ridgeway, 1997).
The theory on statistical discrimination can also explain differential gender discrimination across male- and female-dominated occupations. As noted, most employers are looking for stable employees, and studies have documented that workers’ employment duration is sensitive to the sex typing of the job, so that women who enter a male-dominated occupation and men who enter a female-dominated occupation have disproportionately higher exit risks (Torre, 2014, 2018). Employers might be aware of this association and act accordingly. On closer inspection therefore, the differences between the cultural and the economic-rational perspectives are rather subtle, as both perspectives are compatible with the assumption that gender stereotypes are exogenously given and that employers are looking for the best match between an applicant and a job.3 Both perspectives, therefore, lead us to expect discrimination against the minority sex in sex-typed jobs and to expect to find no prevalence of discrimination in gender-balanced jobs, ceteris paribus. The norm of the ‘ideal worker’, however, leads us to the generic expectation that women are discriminated against, independently of the sex typing of the job.
Theories on discrimination are primarily concerned with individual-level explanations, largely ignoring the role of country-level institutional contexts (Reskin, 2000). However, the ‘opportunity structure for discrimination’ (Petersen and Saporta, 2004) is likely to differ by macro-level factors, which we explain below.
Soweit also zu den theoretischen Ansätzen.
Nun zu den Zahlen:
Und die weitere Tabelle:
Table S1: Proportion of female employees by occupation and country. Percentages.
| Country | Cook | Payroll Clerk | Receptionist | Sales Rep. | Software Dev. | Store Assistant |
| GER | 37.4 | 73.5 | 73.9 | 37.3 | 13.8 | 70.0 |
| NL | 23.3 | 80.0 | 71.2 | 36.5 | 10.8 | 66.5 |
| NOR | 45.0 | 83.7 | 69.0 | 34.8 | 17.3 | 63.9 |
| ESP | 50.7 | 65.7 | 75.9 | 30.8 | 24.3 | 67.0 |
| UK | 73.1 | 77.2 | 72.9 | 43.8 | 16.7 | 62.9 |
| USA | 19.7 | 89.5 | 60.9 | 27.1 | 18.7 | 50.3 |
| Mean tot. | 42.4 | 71.6 | 71.6 | 36.1 | 15.9 | 64.1 |
Der Koch hat einige Schwankungen aus, gerade in den USA scheinen weibliche Kochs nicht so gesucht zu sein, die Rezeptionistin hingegen ist sehr beliebt, ebenso wie die Lohnbuchhalterin, der Handelsvertreter ist eher männlich, der Software Entwickler erst recht. Die Verkäuferin hingegen dann wieder weiblich.
Despite recent changes, on average, women still have lower earnings and worse career prospects. These well-known facts are true according to reliable and national representative data, such as labour force surveys and register data. The key question is why. Broadly speaking, two explanations have been provided. First, women and men might sort into different jobs because of their different educational and occupational choices, and their different work–life balance preferences and constraints, all of which accumulate to different employment trajectories and outcomes. This is the supply-side story. Second, men and women might sort into different jobs because employers discriminate women, particularly in the best-paid jobs. According to this demand-side explanation, hiring discrimination against women would be an important explanation for women’s labour-market disadvantage. Because studies based on observational data cannot empirically adjudicate between supply and demand side explanations, there is a need for field experiments to provide reliable and valid estimates of employers’ hiring discrimination.
Interestingly, the story jointly told by previous field experiments clashes with the conventional account of female disadvantage. It is often the fictitious male applicants, not the females, who are discriminated in hiring processes. In particular, there is evidence that women are favoured in female-dominated occupations. However, the heterogeneity of previous studies, in terms of occupations included, timing of the studies, and at what geographical level (local or national) they took place, makes comparisons difficult. Against this background, we made use of a harmonized field experiment in six countries to provide comparable, reliable, and balanced cross-national documentation of hiring discrimination against men and women.
The field experimental data show no evidence of hiring discrimination against women in any of the occupations in any of the countries included. The countries vary in a number of institutional, economic, and cultural dimensions potentially affecting employers’ likelihood of discriminating against women. We also included occupations varying in skill requirements and customer contact. And, as documented in footnote 7, the manual job content of our occupations vary from high (cooks) to low (payroll clerks). The findings reported in this study therefore constitute an important and robust piece of evidence that young women are not discriminated in the first phase of the hiring process in any of the occupations studied in any of the countries studied.
Second, we found hiring discrimination against men in Germany, the Netherlands, Spain, and the United Kingdom, where male applicants were less likely to receive a callback when they applied for jobs as store assistants (Germany and the Netherlands), receptionists (Spain and Germany), and payroll clerks (Spain and the United Kingdom). We found no hiring discrimination against men in Norway and in the United States. However, when pooling the data, we found no statistically significant differences across countries, perhaps with the exception of the contrast between Germany and the United States.
Understanding Gender Discrimination
With these findings in mind, how can we better understand gender discrimination in hiring? We did not find any support for the generic belief that women are disadvantaged in hiring processes, as implied both in models of cultural stereotypes and statistical discrimination, where employers are assumed to believe that women are potentially unstable workers, more likely to quit their jobs to attend their families and/or generally less committed to their firms. Gender stereotypes where women are seen as mothers and housewives seem less important in hiring processes today than in the past. According to our findings, these stereotypes seem not to operate at all. We suggest a few tentative interpretations of why this is the case. First, most women today are not primarily homemakers. Second, females are more likely to be hiring agents, in particular in female-dominated occupations, and we cannot rule out the possibility of in-group (same gender) favouritism benefiting female candidates. Third, in female occupations, hiring agents might find women more stable employees than men, who might be more likely to pursue a career, thereby leaving the job they were hired for. We should also remember that the job candidates we constructed are young workers with only 4 years of working experience. This means the presented evidence does not preclude the possibility of discrimination against women in hiring, earnings, or promotion opportunities later in the career.
Interestingly, the evidence on hiring discrimination against men would seem compatible with existing theories about gender stereotypes that were formulated to account for women’s disadvantage. Perspectives emphasizing the sex typing of jobs, gender categorization within work organizations, role congruency, and stereotype contents, all seem relevant for explaining discrimination against men in the matching process. Theoretically, these cultural perspectives are also compatible with the economic model of employers as (limited) rational actors who try to find the best match between job tasks and job applicants. If employers perceive certain jobs as more appropriate for women, male applicants, even if formally qualified, may be devaluated because employers believe that they are poor matches for the sex-typed job tasks. For jobs that are not sex-typed, gender stereotypes do not seem to matter in the matching process.
The above-mentioned theories should lead to symmetrical expectations of hiring discrimination against applicants with the ‘wrong sex’ in sex-typed jobs. Thus, they cannot help us understand why women were not discriminated in the male-dominated occupation we included: software developers, an occupation which requires continuous training and where job disruptions are particularly hazardous for employers. To understand this, we can only speculate. It could be that the IT sector is more tolerant, pioneering a new work–life gender-egalitarian culture (Faulkner, 2009, but see Bertogg et al., 2020). Alternatively, given the low proportion of women who enter STEM fields, IT employers might believe female applicants are positively selected in unobserved characteristics. Another possibility is that employers might be nervous that they have implicit or hidden bias against women. As a result, they may overreact and give women advantages in hiring. Whatever the reason is, finding no hiring discrimination against women in IT jobs constitutes an important challenge to both cultural and economic theories of ‘gender’ discrimination.
However surprising, the presented evidence is not at odds with previous research on hiring discrimination. The key to explaining divergent results likely lies in the occupations studied. For balanced studies, including both female- and male-dominated occupations, and gender-neutral occupations, the aggregate outcome would be close to zero gender discrimination in hiring. For more unbalanced studies, like the GEMM study, which includes two clearly female-typed occupations, and only one strongly male-dominated occupation, we might expect an aggregated pattern showing hiring discrimination against men. In principle, the same logic should apply for unbalanced studies including a higher proportion of male dominated occupations, but then we would expect an aggregated pattern of hiring discrimination of females. Yet the findings regarding the male-dominated occupation we included cast doubts on the symmetrical nature of hiring discrimination by gender. Interestingly, when scholars plan to study gender differences in hiring discrimination, we tend to think about discrimination of women, not men, yet previous experiments seem to include more female- than male-dominated occupations. More research including more occupations is needed.
Lack of Cross-National Variation
Despite differences in labour market conditions, family policies, and cultural norms, we found no clear evidence of cross-national variation in hiring discrimination. An explanation might be that the associations of gender stereotypes and jobs, while culturally embedded, are fairly universal across advanced Western economies (but see Supplementary Table S1 for national variations in occupational gender distributions), and hiring agents across these societies are similarly influenced by these views. Given the embeddedness of job-specific gender stereotypes, one might be pessimistic with regard to the possibilities of policy reforms to encourage gender balance. In addition, the implications of our study appear even more serious given that male-dominated occupations related to the industrial society are gradually vanishing. On the other hand, if gender-neutral occupations are growing in size, gender stereotypes will become less important over time. Thus, we have a cultural and a structural argument, and future research would benefit from addressing both arguments.
Naturally, this study has limitations. Field experiments investigate discrimination in the initial stages of the hiring process and do not give information about who gets the jobs, at what wages, and with what career opportunities. Second, the field experiment provides information about the outcomes of job applications for young applicants 22–26 years of age, and we cannot know what the situation would have looked like if we had included older fictitious applicants. Similarly, we have not tested employers’ reactions to applicants with family obligations. It should be noted though, that a Swedish study including older applicants, found no difference in employers’ reactions to mothers and fathers (Bygren, Erlandsson and Gähler, 2017).
Field experiments cannot cover the whole labour market, and the outcomes of these experiments are only representative for the included occupations. The GEMM study includes six occupations, requiring an educational level varying from a high school diploma to a bachelor’s degree. With a limited number of male and female applications within each occupation, we are abstained from analysing in more detail the variation in types of jobs within occupations (e.g. managerial jobs).
We believe that the implications of our findings are important. In particular, we need to update our knowledge of gender discrimination and the belief that women are always the disadvantaged group. This belief might have been correct earlier, but today, at least for the occupations we examined, we found no evidence of hiring discrimination against female job applicants in any of the six countries included. Rather, we observed hiring discrimination against males in female-dominated jobs, whereas female applicants were favoured in female-dominated occupations and not discriminated in the other occupations we included. Future research should explore more in-depth the mechanisms associated with this (reversed) gender gap in hiring discrimination and delineate its boundary conditions.
Also erst einmal ein Experiment, welches nur auf den Einsteigerbereich abstellt. Aber eine interessante Studie, weil sie in diesem Bereich eine Diskriminierung beider Geschlechter untersucht.
Alles Evolution 