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Article

What You Want Is Not Always What You Get: Gender Differences in Employer-Employee Exchange Relationships during the COVID-19 Pandemic

Faculty of Sociology, Bielefeld University, Universitätsstraße 25, D-33615 Bielefeld, Germany
Submission received: 2 June 2021 / Revised: 1 July 2021 / Accepted: 14 July 2021 / Published: 22 July 2021
(This article belongs to the Special Issue Gender Relations at Work: Persistent Patterns and Social Change)

Abstract

:
Relational Inequality Theory (RIT) argues that relational claims-making- the process of employer-employee exchange relationships explicitly regarding negotiations over resources and rewards- is the central mechanism that produces social inequalities at work. Yet, the COVID-19 pandemic has significantly affected employees and employers, possibly altering their behavior in relational claims-making. Hence, this paper aims to explore if long-standing gender inequalities in employer-employee exchange relationships have reproduced or changed during the COVID-19 pandemic. It is examined (1) whether women and men differ in their response to the pandemic regarding expected employer support with further training to work from home (WFH) and (2) whether employers’ decisions on adequate support depend on employees’ gender. The hypotheses were tested using a linked employer-employee dataset (LEEP-B3) with information on German employees’ working conditions before and during COVID-19. OLS regression models predicted no gender differences in training expectations. However, women are more likely to be provided with less training than they expect from their employers. Thus, employers’ decision-making has not been altered, but gender remains an important determinant in relational claims-making, thereby reproducing gender inequalities. Finally, the workforces’ pre-COVID-19 gender ideologies predicted whether mechanisms are mitigated or enhanced. Hence, these findings underline the crucial role of the workplace context in which employer-employee exchange relationships are embedded.

1. Introduction

The COVID-19 pandemic has abruptly and fundamentally changed people’s lives across the globe. The pandemic has tremendously impacted working conditions such as labor market participation, furloughs, working hours, and work from home (WFH) arrangements (Alon et al. 2020; Collins et al. 2020; Gupta et al. 2020). One key aspect in discussions about the pandemic’s consequences is how it has impacted social inequalities, specifically gender (in-)equality. In contrast to previous crises, sectors with high shares of female workers have been adversely affected (e.g., Alon et al. 2020; Hammerschmid et al. 2020). As a result, the employment situation and women’s income—especially mothers—have been disproportionally altered compared to those of men (Collins et al. 2020; Hipp and Bünning 2020; Kristal and Yaish 2020; Reichelt et al. 2020; Rivera and Castro 2021). Moreover, the closure of external childcare facilities and schools has substantially increased care demands, where women, in line with their role as primary caregivers, have taken on the bulk of additional responsibilities (Collins et al. 2020; Kohlrausch and Zucco 2020; Kreyenfeld and Zinn 2021). This has led some scholars to speak of a “patriarchal pandemic” (Chemaly 2020), leading us back to the 1950s (Allemendinger 2020), which is highlighted by research detecting a tendency of re-traditionalization (even among previously egalitarian couples) in the gendered division of labor (Kohlrausch and Zucco 2020). Others suggest that men’s increased tendency to WFH has confronted them with the extent of unpaid household labor (Collins et al. 2020), and that their increased time spent on childcare responsibilities will help the gender revolution in the long run (Alon et al. 2020).
Although crucial, most of these studies focus on the partner- or household-level of exchange relationships and their outcomes, specifically regarding hours spent in paid and unpaid work. However, gender inequalities are likewise produced in employer-employee exchange relationships, particularly in negotiations between these actors within the workplace (Baron and Bielby 1980; Robinson and Rousseau 1994; Tilly 1998; Tomaskovic-Devey and Avent-Holt 2019). Both partner or household and employer-employee exchange relationships are important factors for gender inequality. Nevertheless, the former may simply mirror consensual, temporary coping strategies that have existed only during the pandemic. In contrast, the latter are more likely to map long-term inequality structures rather than short-term adjustments. Further, to understand how the COVID-19 pandemic may be reproducing or altering durable gender inequalities in the labor market, it is necessary to explore whether employer-employee exchange relationships rely on long-standing or new determinants in negotiating access to workplace resources. This is important, as labor market policies aiming to help employees recover from the pandemic need to be designed to address gender inequalities. Particularly if women are structurally disadvantaged in these negotiations.
This paper applies a relational inequality perspective, as the focus lies on exchange relationships between employers and employees at the workplace, which lie at the core of the production of social inequalities (Baron and Bielby 1980; Tilly 1998; Tomaskovic-Devey and Avent-Holt 2019). Following this perspective, inequalities arise due to local negotiations between employers and employees (relational claims-making), where categorical distinctions and workplace characteristics influence which employees receive access to valuable resources and rewards, such as opportunities for further training (Abendroth et al. 2017; Abendroth and Diewald 2019; Baron and Bielby 1980; Tilly 1998; Tomaskovic-Devey and Avent-Holt 2019). Relational claims-making is defined as a two-step process that focuses on employees’ and employers’ actions: (1) employees make claims on workplace recourses or rewards, and subsequently, (2) employers evaluate the legitimacy of these claims and support or dismiss them. Hence, relational claims-making can be considered as part of employer-employee exchange relationships as these actors negotiate about what resources and rewards employees should receive in exchange for their skills, productivity, and categorical group memberships. Most RIT research looks at outcomes of relational claims-making, e.g., wage differences (Avent-Holt and Tomaskovic-Devey 2010; Tomaskovic-Devey and Avent-Holt 2019), but this research attempts to capture the two-step process more closely.
This paper argues that the concept of psychological contracts (e.g., Coyle-Shapiro and Conway 2004; Robinson and Rousseau 1994; Rousseau 1995) can be utilized to approximate the relational claims-making mechanism. The concept of psychological contracts likewise focuses on employer-employee exchange relationships and distinguishes between employees’ expectations to be rewarded with employment gratifications and the adequate fulfillment of these expectations by employers. This is presumed to resemble employees’ claims-making and employers’ evaluation and ratification of posed claims. Therefore, this paper examines (a) if women and men respond differently to the pandemic concerning their expectations of employer support (claims-making) and (b) if employers’ adequate fulfillment of these expectations (ratification of posed claims) rely on long-standing status-based distribution patterns where gender predicts lower workplace resources and rewards for women (e.g., Acker 2006; Avent-Holt and Tomaskovic-Devey 2012; Lükemann and Abendroth 2021). Thus, the analyses can indicate whether gender inequalities are explained by employees’ or employers’ actions in employer-employee exchange relationships.
This paper focuses on employees’ expectations and adequate provision with further training or courses to acquire the skills needed to successfully WFH. Many employers have enforced social distancing measures in response to the pandemic, leading to high shares of employees having transitioned to WFH (e.g., Kohlrausch and Zucco 2020). Further training or courses can provide essential tools to cope with this unique work situation. Exploring gender differences in terms of further training or course provision to WFH is important, as unmet training expectations can widen existing gender inequalities. For instance, if men are more sufficiently provided with the training they expect, they might be better able to maintain their productivity when working from home. Moreover, findings based on the COVID-19 follow up survey indicate that being provided with the WFH training one expects has lowered work-life conflicts during the pandemic. This finding further underscores the importance of investigating who has access to these valuable workplace resources.
Moreover, workplaces differ regarding their history, structure, demographic composition, and culture, each of which influences the extent and type of workplace inequalities (Abendroth and Diewald 2019; Tomaskovic-Devey and Avent-Holt 2019; Peters et al. 2020; Lükemann and Abendroth 2018). Therefore, it is likely that not all workplaces respond equally to the pandemic, but that the pre-COVID-19 workplace culture shapes patterns of gendered unmet training expectations. This paper focuses on the prevalent pre-COVID-19 gender ideologies in the workforce (egalitarian vs. traditional attitudes towards female employment) as an important part of the workplace culture. The dominant gender ideologies are considered to resemble the established salience and status hierarchy employed around the gender-status distinction and thus the role of gender in local employer-employee exchange relationships. Therefore, gender differences in fulfilled training expectations for WFH during the COVID-19 pandemic should vary across workplace contexts characterized by more traditional or egalitarian gender ideologies.
Concluding, the aim of this paper is to explore whether gendered outcomes in employer-employee exchange relationships in negotiations endure or change during the COVID-19 pandemic and thus reproduce or alter gender inequalities at work. Moreover, this paper explores the employee and employer perspectives and can thus disentangle whether (1) women and men respond differently to the pandemic concerning their expectations to be supported with further training or courses to work from home by their employer and (2) if employers rely on the well-established gender hierarchy to decide who will be adequately supported with what they expect. Besides, this paper aims to give insights into how the pre-COVID-19 workplace culture, displayed by the workforces’ gender ideologies, shape gendered unmet training outcomes. Hence, it is necessary to have adequate information on the individual- and workplace-level. To test our assertions the COVID-19 follow-up survey of the LEEP-B3 linked employer-employee dataset of large German workplaces and their workforce is utilized. This dataset provides extensive information on employees’ working conditions before and during the pandemic, enabling us to capture changes in employees’ work situations. Moreover, it includes information on employees’ expectations regarding their employers’ support when transitioning to WFH. Finally, the dataset contains information about employees’ attitudes towards dual-earner couples, making the COVID-19 follow-up survey a well-suited dataset for this study.

2. Gender (In-) Equality and the COVID-19 Pandemic in Germany

Germany, classified as a conservative welfare state regime (Esping-Anderson 1990), has a long tradition of conservative (family) policies, promoting the traditional male breadwinner-female homemaker model (e.g., Aisenbrey et al. 2009; Gangl and Ziefle 2015; Korpi et al. 2013). For instance, Germany had one of the most generous parental leave systems worldwide, with long break entitlements paired with high financial compensation (Ray et al. 2010; Korpi et al. 2013). These long parental leave entitlements have weakened German mothers’ work commitment (Gangl and Ziefle 2015) and led to comparatively long employment breaks after birth (Grunow et al. 2011; Ziefle and Gangl 2014). Another unique characteristic is the joint taxation system for spouses, which provides couples with unequal earnings (single- or one-and-a-half-earner households) with financial benefits (Aisenbrey et al. 2009). Only recently, Germany underwent a paradigm shift in family policy by implementing strategies and measures to foster the reconciliation of work and family (e.g., the expansion of public childcare) and to promote maternal employment (e.g., reduced statutory parental leave entitlements) (Spiess and Wrohlich 2008; Ziefle and Gangl 2014).
These changes have increased female labor market participation, but Germany is still characterized by relatively high shares of women in part-time employment compared to other OECD member states (OECD 2021a). However, although gender differences in labor market participation have declined, they have remained high when considering working hours (OECD 2021b). This is also true when considering gender differences in unpaid work, where women spend more time on household-related tasks than men (Altintas and Sullivan 2016). These gender differences in time spent on housework and childcare are specifically present among parents (Kühhirt 2012; Kreyenfeld and Zinn 2021). In addition, Germany has a high degree of occupational gender segregation in the labor market (Hausmann and Kleinert 2014).
This societal and institutional framework presented the situation of gender inequality in terms of paid and unpaid work when the COVID-19 pandemic hit Germany. Contrasting the recent changes stated above, the German government has mainly relied on families to take responsibility for additional childcare demands during lockdowns (Hipp and Bünning 2020). Hence, due to the closure of schools and daycare centers, as well as social distancing restrictions focused on protecting older people (e.g., grandparents) from the virus, parents have faced the burden of increased childcare demands (Hipp and Bünning 2020).
Turning to the labor market consequences of the COVID-19 pandemic, research has shown substantial variation across country contexts and among heterogeneous employee groups within countries (Adams-Prassl et al. 2020; Hank and Steinbach 2020; Hipp and Bünning 2020; Reichelt et al. 2020). For instance, the risk of unemployment and the probability of being furloughed are significantly lower for German workers than in the UK and the US (Adams-Prassl et al. 2020). Moreover, there are no gender differences in German workers’ unemployment risks and income losses (Adams-Prassl et al. 2020; Reichelt et al. 2020). However, Reichelt and colleagues (Reichelt et al. 2020) demonstrated that women have reduced their working hours more frequently than men and in turn shifted to WFH (see Hipp and Bünning 2020; and Kohlrausch and Zucco 2020 for comparable evidence on changed working hours).
At the household level, women, especially mothers, are primarily responsible for the additional domestic demands due to closed childcare facilities and limited domestic outsourcing; as a response, they have increased their time spent on informal care, homeschooling, and housework (Adams-Prassl et al. 2020; Hank and Steinbach 2020; Hipp and Bünning 2020; Kohlrausch and Zucco 2020). Fathers have likewise increased their contributions to unpaid labor at home, but mothers still take on more of the additional childcare work than fathers (Hank and Steinbach 2020; Hipp and Bünning 2020; Kohlrausch and Zucco 2020). The gendered response to the pandemic is in line with “doing gender” approaches, suggesting that women will engage in housework and childcare to a higher degree than men, as this behavior aligns with and maintains their gender role identity (e.g., West and Zimmerman 1987). Therefore, due to the gendered division of labor, women (and especially mothers) have been pushed to shoulder the bulk of additional housework and childcare demands, thereby reinforcing existing gender inequalities (e.g., Zoch et al. 2020).
Research highlights the heterogeneous responses of couples’ division of labor to the pandemic based on who has had reduced working hours, become unemployed, worked from home, as well as varying educational levels (e.g., Hank and Steinbach 2020; Hipp and Bünning 2020; Kreyenfeld and Zinn 2021; Zoch et al. 2020). Thus, previous research has not detected substantive support for a patriarchal pandemic or a gender convergence in time spent on housework and care demands, but rather a reproduction of the pre-COVID-19 gender patterns. Nevertheless, as women (and especially mothers) have reacted more strongly to the pandemic regarding paid and unpaid working hours, their role as primary caregivers, as well as traditional gender roles, have intensified.

3. Relational Claims-Making

RIT emphasizes that inequalities arise through the process of relational claims-making (Tomaskovic-Devey and Avent-Holt 2019). Employees or groups claim workplace resources such as wages, training, or respect, and powerful actors, such as supervisors or managers, evaluate these claims and grant or dismiss them (Tomaskovic-Devey and Avent-Holt 2019).1 If claims are successful, resources are distributed to the claims-maker, leading to social closure and exploitation (Parkin 1979; Tilly 1998; Tomaskovic-Devey and Avent-Holt 2019; Weber 1978). RIT stresses that both the decision to pose a claim and the legitimacy of claims can be based on employees’ or groups’ skills and productivity. However, the meaning, moral worthiness, and status hierarchies employed around categorical distinctions are the main drivers in the claims-making process (Tomaskovic-Devey and Avent-Holt 2019). Some categorical groups are perceived as superior to others, and cultural status beliefs about groups’ competence, trust, and integrity arise. Higher status groups are given a superordinate position over others (Berger et al. 1972; Fiske et al. 2002; Ridgeway 2014), legitimizing increased social and material distributions to these higher status actors compared to other workers (Parkin 1979; Ridgeway 2014; Tomaskovic-Devey and Avent-Holt 2019; Weber 1978). Hence, higher status actors will make claims more often, and their claims are more likely to be ratified irrespective of their actual skills or productivity, as higher status actors have greater interactional power (Avent-Holt and Tomaskovic-Devey 2010; Ridgeway 2014; Tilly 1998; Tomaskovic-Devey and Avent-Holt 2019). These cognitive biases and status beliefs are salient in social interactions such as claims-making, thereby shaping workplace inequalities between categorically different groups (Acker 2006; Ray 2019; Ridgeway 2014; Tilly 1998; Tomaskovic-Devey and Avent-Holt 2019).

3.1. The Role of Gender in Relational Claims-Making

Gender is one of the most fundamental and salient categorical distinctions that structures societies, work organizations, and social interactions, hierarchically ranking men as superior to women (Acker 2006; Reskin 2000; Ridgeway 2014; West and Zimmerman 1987).2 Since gender can be classified as a status characteristic, cultural status beliefs will be activated despite women’s actual abilities (Correll and Ridgeway 2003; Ridgeway and Correll 2006; Ridgeway 2014).
Past research undeniably supports the idea that gender is a crucial categorical distinction in shaping outcomes of relational claims-making. Women receive lower performance evaluations than men (Castilla 2011; Correll et al. 2007; Ridgeway and Correll 2004), are less represented in positions of higher authority (Stojmenovska and England 2020), receive lower pay (Abendroth et al. 2017; Avent-Holt and Tomaskovic-Devey 2010, 2012), respect (Roscigno et al. 2009), access to employer-provided training (Peters et al. 2021), and have greater unfulfilled expectations in employer-employee exchange relationships (psychological contract violations) (Marx 2019; Reimann 2017). This research outlines the consequences of men’s privileged position in the claims-making process relative to women. Previous research on explicit claims-making and its outcomes, applying an RIT perspective, is scarce. However, two previous studies have examined gender differences in explicit claims-making for career advancements (Lükemann and Abendroth 2018) and gendered outcomes of claims-making (Lükemann and Abendroth 2021). The findings reveal that German mothers make fewer claims for career advancements than fathers, and that women receive fewer rewards (in terms of compensation and mobility) than men, if they pose a claim (Lükemann and Abendroth 2021).3
This research demonstrates that pre-COVID-19, the categorical gender-status distinction was an essential determinant in relational claims-making in both steps: employees’ decisions to pose claims and employers’ evaluation of the posed claims. The question arises if female and male employees hold different expectations regarding further training or course provision to WFH during the COVID-19 pandemic and if employers’ decision-making is still guided by employees’ gender status.

3.2. Employees Claims-Making Decisions and the COVID-19 Pandemic

Why should the COVID-19 pandemic result in gendered differences in employees’ expectations regarding the provision of further training or courses to WFH? As mentioned above, the pandemic has affected men and women differently, which is especially evident in women’s increased time spent on housework and childcare, alongside decreased working hours (Kohlrausch and Zucco 2020; Reichelt et al. 2020). Women may have fewer time and productivity resources to spend on further training or courses than men, which limits their training provision expectations toward their employers. Further, since women’s and men’s responses to the pandemic align with stereotypical views on gender roles, it is likely that the COVID-19 pandemic entails an intensification of gendered status value beliefs. These beliefs pertain to men’s ascribed greater competence, productivity, and suitability for certain work tasks compared to women (Correll et al. 2007; Heilman and Haynes 2005; Hentschel et al. 2019; Ridgeway 2014). Disadvantaged groups, such as women, internalize and accept these cultural status beliefs (Correll and Ridgeway 2003; Ridgeway and Correll 2004, 2006) and subscribe to gender stereotypes (e.g., Hentschel et al. 2019).4 This would imply that women feel less deserving than men to be provided with workplace resources; thus, they anticipate less success if they pose a claim that is portrayed in their lower expectations toward training. Against the backdrop of increased domestic demands and intensified gendered status beliefs, it is hypothesized that:
Hypothesis 1 (H1).
Women will show lower expectations of being provided with further training by their employers than men.

3.3. Employers Claims-Making Decisions and the COVID-19 Pandemic

Catastrophic events, such as wars and pandemics, can mitigate economic inequality by drastically changing society; therefore, the COVID-19 pandemic might function as a great leveler (Scheidel 2017). Moreover, external shocks are crucial moments within workplaces that can create new inclusion and exclusion rules (e.g., Smith 2020). Hence, external changes that interfere with the prevalent logic of workplaces can amplify or mitigate existing social inequalities. However, shocks that are so consequential that they might alter inequality mechanisms established in workplaces are rare since, in general, workplaces are somewhat reluctant to change (e.g., Smith 2020; Stainback et al. 2010; Tomaskovic-Devey and Avent-Holt 2019). Hence, the COVID-19 pandemic offers a unique situation to test whether societal and economic consequences have altered gender inequalities at work. Specifically, does gender remain an important determinant for employers’ decision-making in the claims-making process?
The COVID-19 pandemic has influenced the institutional workplace environment, as it has dramatically increased market competition and pressure. Previous RIT-related research demonstrates that workplace wage inequalities are linked to skill distinctions rather than ascribed status distinctions, such as gender, if workplaces are embedded in more competitive product markets (e.g., Avent-Holt and Tomaskovic-Devey 2010). This is assumed because workplace survival is contingent on worker productivity, thereby legitimizing claims based on skills and qualifications, presumably signaling productivity, and delegitimizing claims based on status distinctions.5 In addition, because men have increased their hours spent on childcare and housework (Hank and Steinbach 2020; Hipp and Bünning 2020), employers might perceive that men face the same productivity and time constraints as women. Thus, perhaps an employer’s decision of who will be adequately provided with the employment gratifications they expect is no longer contingent on employees’ gender status, thereby leveling gender differences in claims-making outcomes.
However, recent research demonstrates that most shocks in history led to an increase in status-based social inequalities (Goda 2018; van Bavel and Scheffer 2021), contradicting the idea of catastrophic events as great levelers (e.g., Scheidel 2017). Research on social stratification and inequality likewise shows that people’s socioeconomic status predicts the risks of COVID-19 infection and death (Bernardi 2020), and that the gender inequality curve in the labor market is not leveled (Kristal and Yaish 2020). Moreover, although fathers have increased their time spent on childcare, mothers have taken on the lion’s share of additional care and housework responsibilities, and have reduced their working hours to a greater extent than men (Adams-Prassl et al. 2020; Hank and Steinbach 2020; Hipp and Bünning 2020). As such, employers might anticipate that men will be more productive and less distracted by household demands than women, and take this into account when deciding who to provide with expected training. Further, as outlined above, the gender-status distinction and gender status beliefs (e.g., Ridgeway 2014), have likely become more salient during the pandemic, reinforcing established gender hierarchies within workplaces. This would suggest that even if women and men do not vary in their expectations to be rewarded with further training or courses, employers may still evaluate their legitimacy to receive these gratifications differently. Consequently, women might exhibit a greater extent of inadequately met training expectations. Hence, it is proposed that:
Hypothesis 2 (H2).
Women will experience higher degrees of unmet training expectations by their employers than men.

3.4. Relational Claims-Making Across Workplace Contexts

How workplaces, and thus employers, respond to the pandemic regarding who is provided with what they expect will most likely be influenced by the pre-COVID-19 workplace culture, specifically the prevalent gender ideologies. The prior gender ideologies dominant in organizations’ workforces display the established, legitimate status hierarchies and gender orders that were present when the pandemic hit. Gender ideologies represent individuals’ beliefs about gender-separate spheres in paid and unpaid work (Davis and Greenstein 2009). They vary across country contexts (Grunow et al. 2018) and regions within countries (Hamjediers 2020; Scarborough and Sin 2020). In line with RIT, previous research also demonstrates that whether a workforce accepts or opposes the idea of women and men as dual breadwinners varies substantially across workplaces (Peters et al. 2020). This underscores the fact that the meaning and value of gender are negotiated locally, creating unique workplace contexts in which claims-making occurs (Tomaskovic-Devey and Avent-Holt 2019). These workplace heterogeneities are fundamental in RIT, which argues that every workplace develops and follows its unique inequality regime (Acker 2006), where the relational power of categorical distinctions varies substantially across workplaces (Abendroth et al. 2017; Abendroth and Diewald 2019; Avent-Holt and Tomaskovic-Devey 2012; Lükemann and Abendroth 2021; Peters et al. 2020; Salzinger 2003; Tomaskovic-Devey and Avent-Holt 2019). In sum, this paper argues that the prevailing gender ideologies within a workforce display the intensity of gendered status beliefs and thereby the salience of gender in local workplace (power) relations and decision-making. As such, the pre-COVID-19 prevalent gender ideologies in each workplace will shape employer-employee exchange relationships during the pandemic. Hence the following is posited:
Hypothesis 3 (H3).
The degree of gendered outcomes of unmet expectations will vary as a function of dominant gender ideologies in the workplace.

4. Data, Measurements, and Method

4.1. The COVID-19 Pandemic in Germany

The following summary of the COVID-19 pandemic and related measures to contain the virus taken by the German government focuses on the observation period of the follow-up survey (October–December 2020). After the first wave of the pandemic in March 2020, the infection numbers in Germany fell and were relatively low from May to July. Infection numbers started to climb again in August and September, and even more in October. In response, the German government began to reinforce its measures in mid-October, mainly focusing on restricting cultural and leisure activities. Additional measures came into force on November 2nd, referred to as lockdown “light.” Measures included social contact restrictions in private life, restaurant closures, prohibitions on recreational, sport, and cultural events, and touristic overnight stays. On 16 December, the retail sector, hardware, drug stores, garden centers, and hairdressers had to close due to the steady rise in infection numbers. During the observation period, schools and daycare centers could remain open and only had to close if COVID-19 infections were detected. However, schools also closed if infection numbers in that region were high, and schools changed to hybrid-teaching models. Thus, although there were no German-wide school closures, many parents had to face external childcare shortages during the observation period.
Moreover, employers responded to government appeals to promote social distancing measures to contain the virus and offered their employees, if possible, the option to WFH, making WFH more common (e.g., Kohlrausch and Zucco 2020). Hence, while WFH was a voluntary option only used by a small share of German-dependent employed workers in 2017 (Grunau et al. 2019), WFH became more widespread during the pandemic.6 Research shows that women transitioned more often than men to WFH (Reichelt et al. 2020).

4.2. Data and Sample

The hypotheses were tested by utilizing the LEEP-B3 COVID-19 follow-up survey. The LEEP-B3 is a dataset constructed as part of a project funded by the German Research Foundation and conducted at Bielefeld University. It is a linked employer-employee panel dataset consisting of 3 waves (Wave 1: 2012/13, Wave 2: 2014/15, and Wave 3: 2018/19) that is representative of large German workplaces and its workforce. The LEEP-B3 is based on administrative records of the German Federal Employment Agency provided by the Institute for Employment Research (IAB) and survey data collected by Bielefeld University (Diewald et al. 2014). The dataset comprises large German companies that employ more than 500 workers who are subject to social security payments (monthly earnings of more than 450 euros). Of all employees in Germany, 19.1% work in large establishments, which make up 0.2% of all German enterprises (Frodermann et al. 2018).7 Establishments and employees were randomly selected to participate in the LEEP-B3 survey. A follow-up survey was carried out in 2020 to capture changes in employees’ working conditions, specifically working from home arrangements, during COVID-19. Moreover, employees were asked about what kinds of support they expected their employers to provide to successfully WFH. The gross sample for the survey incorporated all employees who participated in the third wave and gave permission to be contacted again. Of all contacted employees, 15.9% (810 employees) took part in the follow-up survey. The surveys were conducted via a computer-assisted web interview (CAWI) and took place from October to December 2020, which overlapped with the second wave of the COVID-19 pandemic in Germany. The follow-up survey can be linked to the previous waves of the LEEP-B3 panel to gain more information on respondents’ characteristics, such as gender or educational attainment, and on workplace specifics as industry sector or workforce gender ideologies. After excluding employees with missing information for the dependent variable (17.9%) and employees with missing values for the control variables (16.3%), the final analytical sample consisted of 557 respondents.

4.3. Measurements and Method

4.3.1. Dependent Variable

Employers are obligated to provide certain rewards and resources in exchange for employees’ performance and loyalty at work. This employer-employee exchange relationship is summarized in the psychological contract framework (e.g., Coyle-Shapiro and Conway 2004; Robinson and Rousseau 1994; Rousseau 1995). The psychological contract framework was adapted for the COVID-19 follow-up survey to capture the exceptional conditions during the pandemic. Respondents were asked to rate the extent to which they expected their employer to provide them with further training or courses to acquire the skills needed to WFH.8 Respondents indicated their expectations on a 5-point Likert scale ranging from 1 (“absolutely”) to 5 (“not at all”), which was used to test Hypothesis 1. Then, they were asked to rate the extent to which their employers adequately provided them with training opportunities on the same 5-point scale. The dependent variable to test Hypotheses 2 and 3 was created as the difference between employees’ expectations and perceived fulfillment. This variable ranges from 0–4, where more positive values indicate greater violations.
The reference group consists of employees who feel they received what they expected and received more than expected (see Reimann 2017 for a similar approach). The variable has a mean value of 0.7, signaling that, on average, employees perceive that they get less than they expect from their employer. This corresponds with previous research, which shows that most employees believe their employers do not adequately meet their expectations (Marx 2019; Reimann 2017; Robinson and Rousseau 1994).

4.3.2. Workplace Characteristics

The main variable of interest at the workplace level is the dominant pre-COVID-19 gender ideology within the workforce, measured by respondents’ ratings of the following item: “Men and women should both contribute to household income” in 2018 (the third wave). Respondents were asked to indicate their opinion on a 5-point Likert scale ranging from 1(“applies completely”) to 5 (“does not apply at all”). High values imply more traditional gender ideologies; correspondingly, lower values indicate more egalitarian norms. This information was aggregated to the workplace level to capture the workforce’s average gender ideology in each organization. The gender ideology ranges from 1 to 4.5, with a mean of 2.1, denoting that most workforces hold more egalitarian gender ideologies.
Additional controls included the institutional workplace environment, in which workplaces and thus employer-employee exchange relationships are embedded. The industry sector was measured based on four categories: (1) Education, Health and Public Administration (reference) (2) Manufacturing, (3) Financial and Insurance Services, and (4) Retail, Hospitality, and Transportation. Most workers are employed at companies that offer financial and insurance services; the fewest work in the retail, hospitality, and transportation sectors. Finally, to capture the nature of social relationships at work that shape perceptions of unmet expectations (Reimann 2017), the average supervisors’ and colleagues’ appreciation (“How often do you get appreciation from your colleagues/immediate supervisor?”) and unjust criticism (“How often do you receive unjust criticism from your colleagues/immediate supervisor?”) were aggregated to the workplace level (see Reimann 2017). Respondents could indicate the frequency of appreciation or unjust criticism on a 5-point Likert scale, where high values denote high appreciation and unjust criticism. These measures depict the work climate in which employees are embedded. This is likely to influence the claims-making process by fostering or hindering employees’ decisions to make a claim, as well as colleagues’ and supervisors’ support if a claim is posed. Since the sample only included large enterprises (with more than 500 employees), controlling workplace size was redundant.

4.3.3. Individual Measures

Gender was measured as a binary variable where men are the referent. Of all employees in the sample, 63.5% are men, and 36.5% are women.9 Additional controls included parenthood status (1 = parents), partnership status (1 = partner), age measured in years, higher education (1 = university degree), and supervisory responsibility (1 = yes). Moreover, employees’ degree of job autonomy was captured by an index of the following three items: (1) “Within my working hours, I have control over the sequence of my work activities,” (2) “I can decide how to execute my work tasks,” and (3) “I can define my job objectives.” The job autonomy index ranges from 0 to 12, with higher values signaling higher job autonomy. Further, tenure in one’s current workplace in years, full- and part-time employment (1 = part-time), and how often employees worked overtime before the pandemic (“frequently” [reference], “occasionally,” and “never”) are accounted for in the models.
Moreover, a binary-variable depicts whether employees have previously participated in employer-provided training based on survey information from 2018 (1 = yes). An employee who has been previously invested in by an employer might be more likely to receive the adequate training they expect from their employer. Further, a binary-variable controls for whether employees have worked from home during the COVID-19 pandemic (1 = yes).10 The models also include information on whether employees have worked at home before (1 = yes; telework or home office). A binary-variable captures whether employees’ working conditions have changed due to the COVID-19 pandemic (1 = yes).11 Employees whose working conditions have changed might hold negative feelings toward their employer and therefore rate their support as lower. Finally, if workplaces only informally offer the option to WFH (1 = informal), there might not be an official budget or procedures in place to adequately provide employees with further training or courses.

4.3.4. Analytical Strategy

To investigate Hypothesis 1 that focuses on the individual level (the supply side), OLS regression models were estimated for employees’ expectations to be provided with training to WFH. This paper argues that employees’ expectations should indicate the probability that a claim has been made (or not), resembling the first step in the relational claims-making process. This is assumed because low expectations can signal low need, incentive, or perceived deservingness of training, all predicting that employees will not ask their employer for training. In contrast, high expectations should increase the probability that a claim has been made. Indeed, models estimating the likelihood that employees will speak to their immediate supervisor about career advancements (explicit claims-making), based on previous waves of the LEEP-B3, suggest that higher expectations are associated with higher probabilities of claims-making.
Next, to explore Hypotheses 2 and 3, focusing on the employer level (the demand side) OLS regression models were calculated for the degree of fulfilled expectations. Since employees’ expectations likely mirror the first step in the claims-making process, whether their employer adequately meets their expectations should point to the second step: the employer’s evaluation of posed claims. Finally, to test Hypothesis 3, stating that gendered outcomes will vary as a function of the dominant gender ideologies within the pre-COVID-19 workforce, an interaction term between gender and workforce gender ideologies in organizations was included. To account for employees’ clustering within workplaces, clustered robust standard errors were applied to all models.

5. Results

5.1. Descriptive Statistics

Table 1 portrays the descriptive statistics on all individual measures, while Table 2 captures all workplace characteristics included in the study. 60% of the sample consisted of parents who were, on average, 50 years old at the time of the study and had worked at their current workplace for 11 years. Overall, 39% of employees stated that their employer did not meet their expectations. On average, women had a higher degree of unmet training expectations than men. More men than women had supervisory responsibilities and worked full-time.
Further, the workplace-level descriptive statistics reveal that criticism among colleagues and from one’s immediate supervisors was perceived as being relatively low.

5.2. Multivariate Results

Model 1 in Table 3 displays estimates for testing Hypothesis 1, arguing that women should have lower expectations to be provided with training.12 Estimates in Model 2 (Table 3) were used to test Hypothesis 2, stating that women will show greater violations of expected training support from their employers (higher values indicate greater unmet training expectations).

5.2.1. Differences in Expectations

Estimates reveal that the women and men who took part in the survey did not differ in the extent to which they expected their employer to provide them with further training or courses to WFH (Table 3, Model 1). This finding runs counter to Hypothesis 1. This suggests that women’s greater share of informal care and housework during the pandemic has not lowered their incentive and willingness to participate in further training. Neither do women seem to hold gendered status beliefs, predicting that they feel less deserving of workplace resources than men, predicting lower expectations for training provision. Therefore, women’s and men’s responses to the pandemic do not appear to differ, but they have the same degree of expectations to be provided with further training or courses by their employer.

5.2.2. Differences in Unmet Expectations

Did employers’ decision-making behavior during the COVID-19 pandemic rely on long-standing inequality mechanisms, where gender predicts status-based inequalities in resource and reward distribution? Indeed, the results indicate that although there were no gender differences in training expectations, women tended to have a significantly higher extent of unmet expectations than men (b = 0.227, p < 0.05), despite controlling for sociodemographic, human capital, job, and workplace characteristics (Table 3 Model 2). This finding clearly supports Hypothesis 2, and suggests that gender differences in fulfilled expectations likely resemble employers’ decision-making, rather than individual-level differences in claims-making. Moreover, the COVID-19 pandemic does not seem to have altered the significance of gender in employers’ evaluations of whom to provide with favorable workplace resources. Hence, gender remains an important determinant in relational claims-making, benefitting men and penalizing women, thereby reproducing gender inequalities.
Further, employees with greater job autonomy indicated lower differences in their expectations and provision of further training courses for working from home than employees with lower job autonomy (b = −0.041, p < 0.05). This points to job autonomy as a powerful labor process resource that employees can utilize to garner greater workplace resources (Avent-Holt and Tomaskovic-Devey 2010). In addition, as anticipated, employees with experience in telework or WFH perceived lower violations of employers’ provision of further training courses (b = −0.358, p < 0.001). Employees whose working conditions changed due to COVID-19 perceived greater extents of unmet expectations (b = 0.405, p < 0.001). At the workplace level, the results show that workers employed in Education, Health & Public Administration face higher unmet training expectations than employees in other sectors.

5.2.3. Variation across Workplace Contexts

To test Hypothesis 3, which posits that gender differences in unmet expectations of further training will vary as a function of the dominant gender ideologies within the workforce, a two-way interaction term between gender status and workforce gender ideology was included in the model (Table 4). The interaction coefficient depicts whether the differences in women’s and men’s unmet expectations differed significantly between workplaces with more egalitarian or traditional gender ideologies prevailing in the workforce. A significant, positive interaction effect implies that gender differences in unmet expectations are greater in traditional workplace contexts than in more egalitarian workplaces. For ease of interpretation, the interaction effect is graphically displayed in Figure 1.
The results suggest that for men, more traditional gender ideologies are associated with a steep decline in the magnitude of unmet expectations (b = −0.277, p < 0.05).13 Moreover, men in highly traditional workplace contexts have significantly greater fulfilled training expectations than their counterparts in egalitarian workplace contexts. This implies that if more traditional beliefs about men’s role as main breadwinner were dominant employers more strongly rely on employees’ gender status when distributing resources and rewards. Furthermore, Figure 1 shows that men’s (dashed-line) advantage over women (solid-line) is most salient in highly traditional workplace contexts.
For women, more traditional gender ideologies in the workforce, pre-COVID-19, were associated with greater unmet expectations than men (b = 0.503, p < 0.05). However, female and male employees did not differ in their fulfilled expectations from their employer if they worked in comparatively egalitarian workplace contexts. These findings underline that the degree of gender inequalities (and whether they exist at all) depend on the cultural workplace context, displayed by pre-COVID-19 gender ideologies, in which employer-employee exchange relationships are embedded. Hence, workplaces responded differently to the external shock of the pandemic and mechanisms producing gender inequalities are not omnipresent. Therefore, Hypothesis 3, which states that gender differences in fulfilled training expectations will vary across workplace contexts dependent on the dominant gender ideologies, is supported.
These findings suggest that the prevalent gender ideologies about female and male employment capture the salience and legitimacy of employees’ gender status in local claims-making processes between employees and employers. Hence, workplaces have reacted differently to the pandemic in the (un)equal distribution of further training, because the meaning and value attached to gender—and thus women’s and men’s claims-making power—vary depending on a workplace’s gender ideology. If female employment is valued less than men’s, then employer-employee exchange relationships will likely be more beneficial to men, as they are ascribed a superior position to women. In addition, if men are seen as responsible for earning the household income, workplace resources and rewards may be favorably distributed to them to support their role as male breadwinners. In turn, egalitarian attitudes toward dual-earner couples show that women’s and men’s competencies and suitability in paid work are perceived as equal. In these workplaces, women’s and men’s claims are granted more similarly.

6. Discussion and Conclusions

This study aimed to shed light on whether the COVID-19 pandemic has reproduced or altered durable gender inequality structures in employer-employee exchange relationships. Specifically, the aim was to explore the role of employees’ gender for employees and employers’ actions in relational-claims making. The findings provide evidence on the gendered experiences of employees during the COVID-19 pandemic, regarding their adequate support of further training or courses to WFH. These findings highlight the relevance in applying a gender lens when designing post-COVID-19 labor market policies that aim to counter the negative employment consequences of the pandemic.
This paper argued that the current situation—which has especially led women to decrease their working hours and to take on the lion’s share of housework and childcare demands (e.g., Kohlrausch and Zucco 2020; Reichelt et al. 2020; Zoch et al. 2020)—has confronted women with greater time and productivity constraints than men. Moreover, gendered status value beliefs are likely reinforced (e.g., Ridgeway 2014), as women and men have responded to the pandemic in alignment with their gender role identities (West and Zimmerman 1987). Against this backdrop, it was hypothesized that women exhibit lower training expectations than men. However, the findings suggest that women and men do not differ in their training expectations. This result is in line with previous research indicating that women and men do not differ in their probability of making claims for their career advancements (Lükemann and Abendroth 2018). Therefore, employees’ behavior in relational claims-making does not seem to predict gendered employment outcomes.
Further, the study asked whether gender remains a legitimate basis for employers to distribute resources during the pandemic. The findings imply that women’s expectations are more often not adequately met by their employers compared to men’s expectations. This is in line with past research showing that women receive lower employment rewards after a claim has been posed (Lükemann and Abendroth 2021; Mazei et al. 2015). Moreover, this relates to previous research, which shows that the COVID-19 pandemic has not leveled status-based inequalities, but instead reproduced (or even widened) socioeconomic and gender disparities (Bernardi 2020; Kristal and Yaish 2020). These discrepancies may contribute to pre-existing gender differences in employment outcomes, especially in times of rapid change regarding how work is executed. Suppose that women receive less support than men to adapt to these new work arrangements. In that case, they might lack the skills to uphold their job performance when working from home in the same way as men. Consequently, beliefs about women’s lower productivity might be reinforced, which again legitimizes men’s advantages in employer-employee exchange relationships. In sum, these findings highlight that during the pandemic, employers have applied previously established distribution patterns, where gender is an important determinant of claim ratification. Thus, gender inequalities in employer-employee exchange relationships have remained durable during the global COVID-19 pandemic, not leveling—but rather reproducing—gender inequalities.
At the same time, this research points out ways in which gender inequalities may be altered. The results reveal that the workplace culture in which employer-employee exchange relationships (and thus claims-making) occur is a vital workplace characteristic shaping gender differences in unmet training expectations. The pre-COVID-19 gender ideologies in organization’s moderated gendered outcomes of fulfilled expectations of further training or courses for WFH during the pandemic. Gender differences are non-existent if egalitarian norms, that support both men’s and women’s contributions to household income, prevailed before the pandemic. In contrast, there are significant gaps when more traditional values dominate. Hence, being a woman does not entail disadvantages compared to men per se, but a workforce’s gender ideologies seem pivotal in shaping gendered outcomes in fulfilled expectations. Thus, there is substantial variation in gender differences, dependent on a workforce’s pre-COVID-19 gender ideologies. This finding aligns with previous research, showing that the gender wage gap is lower in regions where more egalitarian gender ideologies prevail in Germany (Hamjediers 2020). Further, the variation across workplace context with different workplace cultures contributes to RIT’s argument that each workplace establishes and follows its own inequality regime that influence relational claims-making outcomes (Acker 2006; Tomaskovic-Devey and Avent-Holt 2019). This finding highlights the importance of examining workplace cultures related to prevalent norms and values to understand how workplace characteristics determine women’s and men’s interactional power to claim workplace resources and rewards.
Overall, this study provides evidence that gender inequalities at work are reproduced during the COVID-19 pandemic, possibly cementing the gender inequalities that have been present previous to the pandemic in Germany. To achieve gender equality post-COVID-19, more gender-egalitarian policies (dual-earner/dual-caregiver) are necessary to break down gendered stereotypes about women’s and men’s roles in paid and unpaid work. This is important as more egalitarian gender ideologies seem to decrease gender differences in employees’ and employers’ employment linked decision-making (see Hamjediers 2020; Lietzmann and Frodermann 2021). Thus, policies need to dismantle the structures that currently hinder or incentivize women to not participate in the labor market to the same extent as men and achieve the same employment outcomes. Moreover, it is essential to support men in their aspiration to take time off work or reduce working hours to care for children. Previous research on policy feedback theory has already demonstrated the pivotal role of public policies for gender (in)equality. For instance, the extension of maternity leave in Germany decreased mothers’ work commitment (Gangl and Ziefle 2015). Moreover, the introduction of the so-called daddy months in Germany in 2007 lead to a stark increase in fathers’ parental leave uptake (Geisler and Kreyenfeld 2012).
This study has a few shortcomings. First, the analyses are based on a cross-sectional sample, which limits claims on causality. An important limitation of this study is that it only accounts for one dimension of the multidimensional gender ideology concept (e.g., Grunow et al. 2018; Hamjediers 2020). Future research should likewise account for a workforce’s attitudes toward women’s and men’s roles in the domestic sphere, as well as mothers’ employment. This enables researchers to gain deeper insight into the pivotal role of dominant gender ideologies as part of the workplace culture. In addition, it could be interesting to explore and contrast some more objective measures such as formalized personnel practices (e.g., formalized career ladders or further training plans) and their effects on gender inequalities at work. Moreover, although this paper argues that the concept of psychological contracts can be used to investigate relational claims-making, it is not a direct measure of whether a claim has been made (or not). However, since additional analyses revealed that high expectations are associated with higher probabilities of speaking with immediate supervisors about one’s career advancement, the authors are relatively certain that these measures indeed capture employees’ claims-making. Moreover, the limited sample size did not allow for analysis of unmet training expectations at the intersection of gender and parenthood. Finally, the national context is important, not only because gender differences vary across country contexts (Abendroth et al. 2014; Aisenbrey et al. 2009; Cooke 2014), as do gender ideologies (Grunow et al. 2018), but also because the COVID-19 pandemic has had different impacts around the globe (Adams-Prassl et al. 2020; Reichelt et al. 2020). Thus, the results are restricted to Germany and workers employed in large companies.
Despite these limitations, this research contributes to the literature on gender inequalities during the COVID-19 pandemic. The findings illustrate, that women are not only burdened more than men with additional housework and childcare but are likewise less likely to be provided with the support they expect from their employers to continue to WFH. Consequently, gender inequalities are reproduced, as gender seems to remain a crucial categorical distinction shaping relational claims-making outcomes. Specifically employers’ decisions on who is granted access to valuable workplace resources and rewards. More research is needed on how employer-employee exchange relationships were affected to understand and anticipate the consequences of the pandemic for gender (in)equalities at work.

Funding

This research was funded by the German Research Foundation (DFG) [grant no.: 373090005]. I acknowledge support for the publication costs by the Open Access Publication Fund of Bielefeld University.

Institutional Review Board Statement

The study was conducted according to the ethical guidelines of the Bielefeld University.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data utilized in this study are not publicly available due to legal data protection regulations but are available upon request.

Conflicts of Interest

The author declares no conflict of interest.

Appendix A

Table A1. Results of logistic regression models on the probability to have participated in the LEEP-B3 follow-up survey (average marginal effects).
Table A1. Results of logistic regression models on the probability to have participated in the LEEP-B3 follow-up survey (average marginal effects).
Workforce Gender Ideologies
BSE
Women−0.028 *0.011
Parents−0.0110.010
Age of the youngest child−0.0010.007
Age in years0.003 *0.011
Tenure in years0.0000.000
Experience in Years0.0000.000
Education (ref. low educational qualifications)
intermediate0.057 ***0.012
high0.125 ***0061
Monthly gross earning0.000 ***0.000
Industry sector (Ref. manufacturing)
Retail, hospitality, and transportation−0.0150.020
Financial and Insurance services0.027 *0.012
Education, health, and public services−0.0100.135
Constant−0.001 ***0.301
N employees5150
Source: LEEP-B3 data. Two-sided test * p < 0.05, *** p < 0.001.
Table A2. Results of linear regression models estimating the association of gender with individual-level characteristics and workforce gender ideologies on employees’ unmet expectations.
Table A2. Results of linear regression models estimating the association of gender with individual-level characteristics and workforce gender ideologies on employees’ unmet expectations.
Model 1Model 2Model 3Model 4
BSEBSESE B
Women0.237 *0.101−0.711 +0.404−0.723 +0.369−0.682 +0.399
Workforce gender ideologies (Ref. egalitarian)−0.0740.086−0.379 **0.129−0.248 *0.126−0.284 *0.138
Standard deviation of Workforce gender ideologies (Ref. egalitarian) 0.0890.134 0.1130.133
Employees gender ideology (Ref. egalitarian) −0.0310.041−0.0430.042
Two-way interactions
Women × traditional workforce gender ideologies 0.460 *0.1900.458 **0.1730.422 *0.189
N employees557557557557
Source: LEEP-B3 data. Models control for: children, partnership status, age in years, job autonomy, higher education, job authority, tenure in years, overtime, employment status, previous employer-provided training, worked from home during COVID-19, previous use of telework/home office, employment changes due to COVID-19, informal home office, work climate, and industry sector. Two-sided test + p < 0.10, * p < 0.05, ** p < 0.01. Note: Model 1 estimates the association of gender ideologies on employees’ unmet expectations. Model 2 includes the variation of the workforces’ gender ideologies. Model 3 adds employees’ gender ideologies, and in Model 4 all aspects are considered simultaneously.
Table A3. Results of linear regression models estimating the association of gender with individual-level characteristics and workforce gender ideologies on employees’ unmet expectations controlling for the share of women within the workplace (Model 1) and the share of employees who used working from home arrangements pre-COVID-19 (Model 2).
Table A3. Results of linear regression models estimating the association of gender with individual-level characteristics and workforce gender ideologies on employees’ unmet expectations controlling for the share of women within the workplace (Model 1) and the share of employees who used working from home arrangements pre-COVID-19 (Model 2).
Model 1Model 2
BSEBSE
Women−0.892 *0.381−0.930 *0.387
Workforce gender ideologies (Ref. egalitarian)−0.272 *0.126−0.239 +0.135
Share women within workplace0.511 *0.2200.568 **0.204
Share employees suage worked from home pre-COVID-19
Two-way interactions
Women × traditional workforce gender ideologies 0.510 **0.1740.509 **0.176
Constant1.571 *0.7152.040 **0.653
N employees557557
Source: LEEP-B3 data. Models control for: children, partnership status, age in years, job autonomy, higher education, job authority, tenure in years, overtime, employment status, previous employer-provided training, worked from home during COVID-19, previous use of telework/home office, employment changes due to COVID-19, informal home office, work climate, and industry sector. Two-sided test + p < 0.10, * p < 0.05, ** p < 0.01.

Notes

1
An example of groups’ claims-making is unions negotiating employment terms like wages or vacation days with employer representatives.
2
Race, class, and age likewise structure interactional group processes in society and at work, thereby determining life outcomes (e.g., Browne and Misra 2003; Ray 2019; Ridgeway 2014).
3
Research in other fields that focus on negotiations (such as management and psychology) likewise suggest that if women engage in wage negotiations, they receive lower returns than men (for a comprehensive overview, see Mazei et al. 2015).
4
For example, women and men do not differ in their perceptions of fair pay; both assign men higher wages than women (Adriaans et al. 2020; Auspurg et al. 2017.)
5
This corresponds to Becker’s (1975) argument that competition should reduce wage discrimination as firms reward productivity, not ascribed categorical distinctions.
6
Of all German employees, 28% stated that they worked at least sometimes from home, with full days working from home being the exception (Grunau et al. 2019.)
7
Since the dataset is comprised of large companies, gender differences might be underestimated, as these workplaces have more training resources at their disposal (Bassanini et al. 2005).
8
Such training or courses might include introductions to new software, personal and time management, and the organization of work tasks.
9
Selectivity analyses revealed that men, higher educated, older employees, non-supervisors, and employees working in the credit and insurance sectors were more likely to have participated in the follow-up survey. However, effects were relatively low, except among the highest educated, who were 12.5% more likely than the least educated to have taken part (see Table A1 in the Appendix A).
10
Models only including employees who have worked from home during the pandemic yielded equivalent results, underlining the robustness of the main findings.
11
A binary variable was created with employees who stated that nothing has changed (72%) as the referent. All other employees who have had reduced hours, worked overtime more often, or taken time off as compensation for overtime were coded as 1.
12
Ordered logit models produced equivalent results.
13
Additional analyses show that employees’ expectations are, on average, not met more in workplaces with egalitarian gender ideologies than in workplaces with more traditional ideologies. Further, models that included controls for employees’ gender ideologies and the standard deviation of workforces’ gender ideologies, capturing the gender ideology consistency among the workforce, confirm the robustness of the main results (Table A2, Appendix A). Robustness checks, including the share of women in the workplace and the share of employees who have used working from home arrangements pre-COVID-19, produced equivalent results (Table A3, Appendix A).

References

  1. Abendroth, Anja-Kristin, and Martin Diewald. 2019. Auswirkungen von Teleheimarbeit auf geschlechtsspezifische Einkommensungleichheiten in Arbeitsorganisationen. Kölner Zeitschrift für Soziologie & Sozialpsychologie 71. [Google Scholar] [CrossRef]
  2. Abendroth, Anja-Kristin, Matt Huffman, and Judith Treas. 2014. The Parity Penalty in Life Course Perspective. American Sociological Review 79. [Google Scholar] [CrossRef]
  3. Abendroth, Anja-Kristin, Silvia Maja Melzer, Alexandra Kalev, and Donald Tomaskovic-Devey. 2017. Women at Work. International Labour Review 70. [Google Scholar] [CrossRef]
  4. Acker, Joan. 2006. Inequality Regimes. Gender & Society 20. [Google Scholar] [CrossRef] [Green Version]
  5. Adams-Prassl, Abigail, Teodora Boneva, Marta Golin, and Christopher Rauh. 2020. Inequality in the impact of the coronavirus shock: Evidence from real time surveys. Journal of Public Economics 189. [Google Scholar] [CrossRef]
  6. Adriaans, Jule, Carsten Sauer, and Katharina Wrohlich. 2020. Gender Pay Gap in den Köpfen: Männer und Frauen bewerten niedrigere Löhne für Frauen als gerecht. DIW Wochenbericht 10. [Google Scholar] [CrossRef]
  7. Aisenbrey, Silke, Marie Evertsson, and Daniela Grunow. 2009. Is There a Career Penalty for Mothers’ Time Out? A Comparison of Germany, Sweden and the United States. Social Forces 88. [Google Scholar] [CrossRef]
  8. Allemendinger, Jutta. 2020. Zurück in alte Rollen. Corona bedroht die Geschlechtergerechtigkeit. WZB Mitteilungen 168: 45–47. [Google Scholar]
  9. Alon, Titan, Matthias Doepke, Jane Olmstead-Rumsey, and Michèle Tertilt. 2020. The impact of COVID-19 on gender equality. In National Bureau of Economic Research. Working Paper No. 2697. Available online: https://www.nber.org/papers/w26947 (accessed on 17 July 2021).
  10. Altintas, Evrim, and Oriel Sullivan. 2016. Fifty years of change updated: Cross-national gender convergence in housework. Demographic Research 35. [Google Scholar] [CrossRef] [Green Version]
  11. Auspurg, Katrin, Thomas Hinz, and Carsten Sauer. 2017. Why Should Women Get Less? Evidence on the Gender Pay Gap from Multifactorial Survey Experiments. American Sociological Review 82. [Google Scholar] [CrossRef] [Green Version]
  12. Avent-Holt, Dustin, and Donald Tomaskovic-Devey. 2010. The Relational Basis of Inequality. Work and Occupations 37. [Google Scholar] [CrossRef]
  13. Avent-Holt, Dustin, and Donald Tomaskovic-Devey. 2012. Relational Inequality: Gender Earnings Inequality in U.S. and Japanese Manufacturing Plants in the Early 1980s. Social Forces 91. [Google Scholar] [CrossRef]
  14. Baron, James N., and William T. Bielby. 1980. Bringing the Firms Back in: Stratification, Segmentation, and the Organization of Work. American Sociological Review 45. [Google Scholar] [CrossRef]
  15. Bassanini, Andrea, Alison Booth, Giorgio Brunello, Maria De Paola, and Edwin Leuven. 2005. Workplace Training in Europe. IZA Discussion Paper 2005: 1640. [Google Scholar]
  16. Becker, Gary S. 1975. Human Capital. New York: National Bureau of Economic Research. [Google Scholar]
  17. Berger, Joseph, Benard P. Cohen, and Morris Zelditch Jr. 1972. Status Characteristics and Social Interaction. American Sociological Review 37. [Google Scholar] [CrossRef]
  18. Bernardi, Fabrizio. 2020. Pandemics… the Great Leveler? EUIdeas, Evidence-Driven Contributions on Social, Political, Legal, and Economic Issues. Available online: https://euideas.eui.eu/2020/04/28/pandemics-the-great-leveler/ (accessed on 15 July 2021).
  19. Browne, Irene, and Joya Misra. 2003. The Intersection of Gender and Race in the Labor Market. Annual Review of Sociology 29. [Google Scholar] [CrossRef]
  20. Castilla, Emilio J. 2011. Bringing Managers Back In: Managerial Influences on Workplace Inequality. American Sociological Review 76. [Google Scholar] [CrossRef]
  21. Chemaly, Soraya. 2020. Coronavirus Could Hurt Women the Most: Here’s How to Prevent a Patriarchal Pandemic. Available online: https://www.nbcnews.com/think/opinion/coronavirus-could-hurt-women-most-here-s-how-prevent-patriarchal-ncna1186581 (accessed on 27 May 2021).
  22. Collins, Caitlyn, Liana C. Landivar, Leah Ruppanner, and William J. Scarborough. 2020. COVID-19 and the gender gap in work hours. Gender, Work & Organization 28. [Google Scholar] [CrossRef]
  23. Cooke, Lynn Prince. 2014. Gendered Parenthood Penalties and Premiums across the Earnings Distribution in Australia, the United Kingdom, and the United States. European Sociological Review 30. [Google Scholar] [CrossRef] [Green Version]
  24. Correll, Shelley J., and Cecilia L. Ridgeway. 2003. Expectation States Theory. In Handbooks of Sociology and Social Research. Handbook of Social Psychology. Edited by John DeLamater. Dordrecht: Kluwer Academic; Plenum Publishers, pp. 29–51. [Google Scholar]
  25. Correll, Shelley J., Stephen Benard, and In Paik. 2007. Getting a Job: Is There a Motherhood Penalty? American Journal of Sociology 112. [Google Scholar] [CrossRef] [Green Version]
  26. Coyle-Shapiro, Jacqueline A.-M., and Neil Conway. 2004. The Employment Relationship through the Lens of Social Exchange. In The Employment Relationship: Examining Psychological and Contextual Perspectives. Edited by Jacqueline A.-M. Coyle-Shapiro, Lynn M. Shore, Susan M. Taylor and Lois Tetrick. Oxford: Oxford University Press, pp. 5–28. [Google Scholar]
  27. Davis, Shannon N., and Theodore N. Greenstein. 2009. Gender Ideology: Components, Predictors, and Consequences. Annual Review of Sociology 35. [Google Scholar] [CrossRef] [Green Version]
  28. Diewald, Martin, Reinhard Schunck, Anja-Kristin Abendroth, and Silvia Maja Melzer. 2014. The SFB882-B3 Linked Employer- Employee Panel Survey (LEEP-B3). Schmollers Jahrbuch 134. [Google Scholar] [CrossRef]
  29. Esping-Anderson, Gøsta. 1990. Three Worlds of Welfare Capitalism. Princeton: Princeton University Press. [Google Scholar]
  30. Fiske, Susan T., Amy J. C. Cuddy, Peter Glick, and Jun Xu. 2002. A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition. Journal of Personality and Social Psychology 82. [Google Scholar] [CrossRef]
  31. Frodermann, Corinna, Alexandra Schmucker, and Dana Müller. 2018. Entgeltgleichheit zwischen Frauen und Männern in mittleren und großen Betrieben. IAB Forschungsbericht 3. [Google Scholar]
  32. Gangl, Markus, and Andrea Ziefle. 2015. The Making of a Good Woman: Extended Parental Leave Entitlements and Mothers’ Work Commitment in Germany. American Journal of Sociology 2018: 121. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Geisler, Esther, and Michaela Kreyenfeld. 2012. How policy matters: Germany’s parental leave benefit reform and fathers’ behavior 1999–2009. Max Planck Institute for Demographic Research 21. [Google Scholar] [CrossRef]
  34. Goda, Thomas. 2018. The global concentration of wealth. Cambridge Journal of Economics 42. [Google Scholar] [CrossRef]
  35. Grunau, Philipp, Kevin Ruf, Susanne Steffes, and Stefanie Wolter. 2019. Mobile Arbeitsformen aus Sicht von Betrieben und Beschäftigten: Homeoffice bietet Vorteile, hat aber auch Tücken. Nürnberg: IAB-Kurzbericht, pp. 1–12. [Google Scholar]
  36. Grunow, Daniela, Silke Aisenbrey, and Marie Evertsson. 2011. Familienpolitik, Bildung und Berufskarrieren von Müttern in Deutschland, USA und Schweden. Kölner Zeitschrift für Soziologie & Sozialpsychologie 66. [Google Scholar] [CrossRef] [Green Version]
  37. Grunow, Daniela, Katia Begall, and Sandra Buchler. 2018. Gender Ideologies in Europe: A Multidimensional Framework. Journal of Marriage and Family 80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Gupta, Sumedha, Laura Montenovo, Thuy Nguyen, Felipe L. Rojas, Ian M. Schmutte, Kosali I. Simon, Bruce A. Weinberg, and Coady Wing. 2020. Effects of Social Distancing Policy on Labor Market Outcomes. NBER Working Paper 17180. [Google Scholar] [CrossRef]
  39. Hamjediers, Maik. 2020. Can Gender Ideologies Account for Regional Variation of the Gender Pay Gap in Germany? SocArXiv. [Google Scholar] [CrossRef]
  40. Hammerschmid, Anna, Julia Schmieder, and Katharina Wrohlich. 2020. Frauen in Corona-Krise stärker am Arbeitsmarkt betroffen als Männer. DIW Aktuell 42: 1–7. [Google Scholar]
  41. Hank, Karsten, and Anja Steinbach. 2020. The virus changed everything, didn’t it? Couples’ division of housework and childcare before and during the Corona crisis. Journal of Family Research 33. [Google Scholar] [CrossRef]
  42. Hausmann, Ann-Christin, and Corinna Kleinert. 2014. Occupational sex segregation in the labor market: Male and female domains nearly unchanged. IAB-Kurzbericht 9: 1–8. [Google Scholar]
  43. Heilman, Madeline E., and Michelle C. Haynes. 2005. No Credit Where Credit Is Due: Attributional Rationalization of Women’s Success in Male-Female Teams. Journal of Applied Psychology 90. [Google Scholar] [CrossRef] [Green Version]
  44. Hentschel, Tanja, Madeline E. Heilman, and Claudia V. Peus. 2019. The Multiple Dimensions of Gender Stereotypes: A Current Look at Men’s and Women’s Characterizations of Others and Themselves. Frontiers in Psychology 10. [Google Scholar] [CrossRef] [PubMed]
  45. Hipp, Lena, and Mareike Bünning. 2020. Parenthood as a driver of increased gender inequality during COVID-19? Exploratory evidence from Germany. European Societies 23. [Google Scholar] [CrossRef]
  46. Kohlrausch, Bettina, and Aline Zucco. 2020. Die Corona-Krise Trifft Frauen Doppelt. Düsseldorf: WSI Policy Brief, pp. 1–14. [Google Scholar]
  47. Korpi, Walter, Tommy Ferrarini, and Stefan Englund. 2013. Women’s Opportunities under Different Family Policy Constellations: Gender, Class, and Inequality Tradeoffs in Western Countries Re-examined. Social Politics: International Studies in Gender, State & Society 20. [Google Scholar] [CrossRef]
  48. Kreyenfeld, Michaela, and Sabine Zinn. 2021. Coronavirus and care: How the coronavirus crisis affected fathers’ involvement in Germany. Demographic Research 44. [Google Scholar] [CrossRef]
  49. Kristal, Tali, and Meir Yaish. 2020. Does the coronavirus pandemic level the gender inequality curve? (It doesn’t). Research in Social Stratification and Mobility 68. [Google Scholar] [CrossRef]
  50. Kühhirt, Michael. 2012. Childbirth and the Long-Term Division of Labour within Couples: How do Substitution, Bargaining Power, and Norms affect Parents’ Time Allocation in West Germany? European Sociological Review 28. [Google Scholar] [CrossRef]
  51. Lietzmann, Torsten, and Corinna Frodermann. 2021. Gender Role Attitudes and Labour Market Behaviours: Do Attitudes Contribute to Gender Differences in Employment in Germany? Work, Employment and Society. [Google Scholar] [CrossRef]
  52. Lükemann, Laura, and Anja-Kristin Abendroth. 2018. Women in the German Workplace: What Facilitates or Constrains Their Claims-Making for Career Advancement? Social Sciences 7: 214. [Google Scholar] [CrossRef] [Green Version]
  53. Lükemann, Laura, and Anja-Kristin Abendroth. 2021. The Gendered Character of Career Advancements and Rewards: A Longitudinal Analysis. Manuscript submitted for publication. [Google Scholar]
  54. Marx, Charlotte. 2019. Die Rolle von Organisationalen Policies für die Geschlechterordnung: Der Einfluss von Gleichstellungs- und Vereinbarkeitsmaßnahmen auf Geschlechterunterschiede im Psychologischen Vertrag. In Ordnung(en) der Arbeit. Edited by Janina Henkes, Maximilian Hugendubel, Christina Meyn and Christofer Schmidt. Münster: Westfälisches Dampfboot, pp. 93–109. [Google Scholar]
  55. Mazei, Jens, Joachim Hüffmeier, Philipp A. Freund, Alice F. Stuhlmacher, Lena Bilke, and Guido Hertel. 2015. A meta-analysis on gender differences in negotiation outcomes and their moderators. Psychological Bulletin 141. [Google Scholar] [CrossRef]
  56. OECD Data. 2021a. Part-Time Employment Rate. Available online: https://data.oecd.org/emp/part-time-employment-rate.htm (accessed on 23 June 2021).
  57. OECD Stat. 2021b. Employment: Time Spent in Paid and Unpaid Work, by Sex. Available online: https://stats.oecd.org/index.aspx?queryid = 54757# (accessed on 23 June 2021).
  58. Parkin, Frank. 1979. Marxism and Class Theory: A Bourgeois Critique. New York: Columbia University Press. [Google Scholar]
  59. Peters, Eileen, Jil Drobe, and Anja-Kristin Abendroth. 2020. Gleichheit durch Gleichstellungsmaßnahmen? Kölner Zeitschrift für Soziologie & Sozialpsychologie 72. [Google Scholar] [CrossRef]
  60. Peters, Eileen, Silvia M. Melzer, and Lynn Prince Cooke. 2021. Gendered Parenthood Gaps in Employer-Provided Training: The Role of Immediate Supervisors. Manuscript submitted for publication. [Google Scholar]
  61. Ray, Victor. 2019. A Theory of Racialized Organizations. American Sociological Review 84. [Google Scholar] [CrossRef]
  62. Ray, Rebecca, Janet C. Gornick, and John Schmitt. 2010. Who cares? Assessing generosity and gender equality in parental leave policy designs in 21 countries. Journal of European Social Policy 20. [Google Scholar] [CrossRef]
  63. Reichelt, Malte, Kinga Makovi, and Anahit Sargsyan. 2020. The impact of COVID-19 on gender inequality in the labor market and gender-role attitudes. European Societies 23. [Google Scholar] [CrossRef]
  64. Reimann, Mareike. 2017. What contributes to psychological contract breach? Investigating a multilevel approach on the interplay of organizational and individual factors. Psychosociological Issues in Human Resource Management 5. [Google Scholar] [CrossRef]
  65. Reskin, Barbara F. 2000. The Proximate Causes of Employment Discrimination. Contemporary Sociology 29. [Google Scholar] [CrossRef]
  66. Ridgeway, Cecilia L. 2014. Why Status Matters for Inequality. American Sociological Review 79. [Google Scholar] [CrossRef] [Green Version]
  67. Ridgeway, Cecilia L., and Shelley J. Correll. 2004. Unpacking the Gender System. Gender & Society 18. [Google Scholar] [CrossRef]
  68. Ridgeway, Cecilia L., and Shelley J. Correll. 2006. Consensus and the Creation of Status Beliefs. Social Forces 85. [Google Scholar] [CrossRef]
  69. Rivera, Valentina, and Francisca Castro. 2021. Between Social Protests and a Global Pandemic: Working Transitions under the Economic Effects of COVID-19. Social Sciences 10: 145. [Google Scholar] [CrossRef]
  70. Robinson, Sandra L., and Denise M. Rousseau. 1994. Violating the psychological contract: Not the exception but the norm. Journal of Organizational Behavior 15. [Google Scholar] [CrossRef]
  71. Roscigno, Vincent J., Steven H. Lopez, and Randy Hodson. 2009. Supervisory Bullying, Status Inequalities and Organizational Context. Social Forces 87. [Google Scholar] [CrossRef]
  72. Rousseau, Denise M. 1995. Psychological Contracts in Organizations: Understanding Written and Unwritten Agreements. Thousand Oaks: Sage. [Google Scholar]
  73. Salzinger, Leslie. 2003. Gender in Production: Making Workers in Mexico’s Global Factories. Berkley and London: University of California Press. [Google Scholar]
  74. Scarborough, William J., and Ray Sin. 2020. Gendered Places: The Dimensions of Local Gender Norms across the United States. Gender & Society 34. [Google Scholar] [CrossRef]
  75. Scheidel, Walter. 2017. The Great Leveler: Violence and the Global History of Inequality from the Stone Age to the Present. Princeton and Oxford: Princeton University Press. [Google Scholar]
  76. Smith, Chris M. 2020. Exogenous Shocks, the Criminal Elite, and Increasing Gender Inequality in Chicago Organized Crime. American Sociological Review 85. [Google Scholar] [CrossRef]
  77. Spiess, Katharina C., and Katharina Wrohlich. 2008. The Parental Leave Benefit Reform in Germany: Costs and Labour Market Outcomes of Moving towards the Nordic Model. Population Research and Policy Review 27. [Google Scholar] [CrossRef] [Green Version]
  78. Stainback, Kevin, Donald Tomaskovic-Devey, and Sheryl Skaggs. 2010. Organizational Approaches to Inequality: Inertia, Relative Power, and Environments. Annual Review of Sociology 36. [Google Scholar] [CrossRef]
  79. Stojmenovska, Dragana, and Paula England. 2020. Parenthood and the Gender Gap in Workplace Authority. European Sociological Review. [Google Scholar] [CrossRef]
  80. Tilly, Charles. 1998. Durable Inequality. Berkeley: University of California Press. [Google Scholar]
  81. Tomaskovic-Devey, Donald, and Dustin Avent-Holt. 2019. Relational Inequalities. An Organizational Approach. Oxford: Oxford University Press. [Google Scholar]
  82. van Bavel, Bas, and Marten Scheffer. 2021. Historical effects of shocks on inequality: The great leveler revisited. Humanities and Social Sciences Communications 8. [Google Scholar] [CrossRef]
  83. Weber, Max. 1978. Economy and Society: An Outline of Interpretive Sociology. Edited by Guenther Roth and Claus Wittich. Translated by Frischhoff E. Berkeley. Berkeley: University of California Press. [Google Scholar]
  84. West, Candace, and Don H. Zimmerman. 1987. Doing Gender. Gender & Society 1. [Google Scholar] [CrossRef]
  85. Ziefle, Andrea, and Markus Gangl. 2014. Do Women Respond to Changes in Family Policy? A Quasi-Experimental Study of the Duration of Mothers’ Employment Interruptions in Germany. European Sociological Review 30. [Google Scholar] [CrossRef]
  86. Zoch, Gundula, Ann-Christin Bächmann, and Basha Vicari. 2020. Who cares when care closes? Care-arrangements and parental working conditions during the COVID-19 pandemic in Germany. European Societies 23. [Google Scholar] [CrossRef]
Figure 1. Gender differences in unmet further training expectations and workforce gender ideologies. Note: Results based on Table 4. 95% confidence bands for one-tailed tests.
Figure 1. Gender differences in unmet further training expectations and workforce gender ideologies. Note: Results based on Table 4. 95% confidence bands for one-tailed tests.
Socsci 10 00281 g001
Table 1. Individual-level descriptive statistics (N = 557).
Table 1. Individual-level descriptive statistics (N = 557).
MenWomen
MeanSDMin.Max.MeanSDMin.Max.
Extent of unmet expectations (0 = adequately met)0.590.98040.881.1304
Children (0 = no)0.600.49010.590.4901
Age in years47.678.87225847.668.602858
Partner (0 = no)0.870.34010.860.3401
Job autonomy index (0 = low autonomy)8.352.170128.302.83012
Supervisory responsibilities (0 = no)0.400.49010.210.4101
Higher education (0 = no)0.540.50010.540.5001
Tenure in years11.348.750.539.710.748.350.534.5
Part-time employment (0 = no)0.050.23010.430.5001
Frequency of overtime (0 = frequently)1.500.63021.320.6402
Participation in employer-provided training before 2020 (0 = no)0.800.40010.830.3801
Previous use of telework/home office (0 = no)0.330.47010.330.4701
Change in employment conditions due to COVID-19 (0 = no)0.270.45010.290.4501
Informal home office (0 = no)0.570.50010.480.5001
Worked from home during COVID-19 (0 = no)0.780.42010.720.4501
Table 2. Workplace-level descriptive statistics.
Table 2. Workplace-level descriptive statistics.
Workplace Characteristics
MeanSDMin.Max.
Criticism from supervisor3.240.371.54
Criticism from colleagues3.350.331.54
Appreciation from colleagues2.110.410.53.5
Appreciation from supervisor2.380.380.74
Industry sectors2.511.0414
Workforce gender ideologies2.120.5014.5
Table 3. The results of linear regression models, estimating the association of individual- and workplace-level characteristics regarding the expectation to be provided with training (Model 1) and unmet expectations (Model 2).
Table 3. The results of linear regression models, estimating the association of individual- and workplace-level characteristics regarding the expectation to be provided with training (Model 1) and unmet expectations (Model 2).
Model 1Model 2
ExpectationUnmet Expectations
BSEBSE
Women−0.0980.1190.227 *0.104
Individual controls
Children (1 = yes)−0.0860.123−0.0180.096
Partnership status (1 = partner)−0.443 **0.1470.0620.129
Age in years−0.0020.007−0.0030.005
Job autonomy index (ref. low autonomy)0.0430.024−0.041 *0.018
Supervisory responsibilities (1 = yes)0.1900.107−0.199 *0.083
Higher education (1 = yes)0.1960.125−0.0210.091
Tenure in years−0.0070.006−0.0050.006
Overtime (ref. frequently)
  occasionally−0.1160.182−0.1610.155
  never−0.0720.1640.0040.152
Part-time work (1 = yes)−0.0450.1390.0010.119
Previous participation in employer-provided training (1 = yes)−0.1340.133−0.0960.117
Previous use of telework/home office (1 = yes)0.405 **0.147−0.358 ***0.091
Worked at home during COVID-190.692 ***0.154−0.321 **0.113
Change of employment conditions due to COVID-19 (1 = yes)−0.354 **0.1330.405 ***0.103
Informal home office in workplace (1 = yes)0.0540.1150.0900.090
Workplace controls
Work climate
Criticism from supervisor−0.2200.1900.3140.175
Criticism from colleagues0.0790.217−0.1000.205
Appreciation from supervisor
Appreciation from colleagues0.395 *0.179−0.1280.161
Industry sector (ref. Education, Health & Public Administration)−0.2730.186−0.1560.148
  Manufacturing0.3850.199−0.508 **0.170
  Retail, Hospitality, and
Transportation
0.586 *0.238−0.700 ***0.203
  Financial and Insurance services0.476 **0.181−0.628 ***0.161
Constant3.458 ***0.7001.486 **0.523
N employees557557
Source: LEEP-B3 data. One-sided test * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 4. The results of linear regression models, estimating the association of gender with workforce gender ideologies in relation to employees’ unmet expectations.
Table 4. The results of linear regression models, estimating the association of gender with workforce gender ideologies in relation to employees’ unmet expectations.
Workforce Gender Ideologies
BSE
Women−0.812 *0.399
Workforce gender ideologies (Ref. egalitarian)−0.277 *0.135
Two-way interactions
Women × traditional workforce gender ideologies0.503 **0.183
Constant2.144 ***0.577
N employees557
Source: LEEP-B3 data. Models control for: children, partnership status, age in years, job autonomy, higher education, job authority, tenure in years, overtime, employment status, previous employer-provided training, worked from home during COVID-19, previous use of telework/home office, employment changes due to COVID-19, informal home office, work climate, and industry sector. One-sided test * p < 0.05, ** p < 0.01, *** p < 0.001.
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Peters, E. What You Want Is Not Always What You Get: Gender Differences in Employer-Employee Exchange Relationships during the COVID-19 Pandemic. Soc. Sci. 2021, 10, 281. https://0-doi-org.brum.beds.ac.uk/10.3390/socsci10080281

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Peters E. What You Want Is Not Always What You Get: Gender Differences in Employer-Employee Exchange Relationships during the COVID-19 Pandemic. Social Sciences. 2021; 10(8):281. https://0-doi-org.brum.beds.ac.uk/10.3390/socsci10080281

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Peters, Eileen. 2021. "What You Want Is Not Always What You Get: Gender Differences in Employer-Employee Exchange Relationships during the COVID-19 Pandemic" Social Sciences 10, no. 8: 281. https://0-doi-org.brum.beds.ac.uk/10.3390/socsci10080281

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