All that he wants is another culture: diversity- and inclusion-oriented cultures create asymmetric stress outcomes by gender Open Access

The relationship between organizational culture and employee stress represents a critical concern for occupational health psychology (Bakker and Demerouti, 2017; Yip et al., 2021). Workplace stress has a significant impact on employee health, resulting in annual stress-related healthcare expenditures and lost productivity costs of between $125 billion and $190 billion in the United States alone, as well as approximately 120,000 annual deaths (Goh et al., 2016). While organizations have, over the years, turned to diversity and inclusion initiatives to create healthier work environments, surprisingly little is known about whether these cultures differentially affect stress outcomes across employee groups. This gap is particularly concerning, given the recent backlash against DEI practices (Burnett and Aguinis, 2024), which has intensified debates about the actual versus intended impacts of such initiatives.

What we do know is that organizational culture can profoundly influence employee stress and well-being (Lopez-Martin and Topa, 2019; Santos et al., 2012; Singh and Jha, 2014). For example, Lopez-Martin and Topa (2019) found that an organizational culture focused on goal setting may have a detrimental effect on employee well-being as it emphasizes competitiveness rather than cooperation. In contrast, a culture focused on rules is likely to increase employee well-being by providing a sense of predictability within the organization. Similarly, other studies have shown that a cooperative organizational culture, which focuses on relationships and innovation, is positively associated with psychological well-being at work (Santos et al., 2012) and that a clan organizational culture improves employees' psychological safety to a greater extent than a hierarchy organizational culture (Dheer et al., 2026). In short, organizational culture matters, with a common perception that inclusive cultures benefit all employees equally, particularly those they are designed to support, i.e. minority groups including women, and that “organizations must ensure that all employees feel included and valued, regardless of the dimensions on which they differ from others” (Şahin et al., 2025).

A gap, however, remains between the rhetoric of a diversity- and inclusion-oriented culture's (DIOC) positive impact on employees' inclusion and sense of belonging at work and the reality that employees encounter within DIOCs. The findings from a recent multidisciplinary meta-review on organizational diversity and inclusion interventions (Zhao et al., 2025) emphasize the need for greater organizational focus on inclusion-improving actions and for setting more practical and realistic expectations about the extent of change that can be attained.

Acknowledging the multifaceted nature of diversity and the multitude of intersectional variables across individuals, Şahin et al.’s (2025) study found that the greater the differences between people, the greater the perceived inclusion gap. However, they also found that this negative relationship (perceived differences between individuals and perceived inclusion within the organization) was often attenuated by a positive perception of the organizational inclusion climate. Their study reinforces the paradoxical nature of DIOCs, where on the one hand “As organizations become increasingly diverse, … a growing number of employees are or feel dissimilar to their coworkers” (Şahin et al., 2025), and, on the other, that, “through fostering inclusion, individuals can fully participate and belong in organisations” (Carr, 2026, p. 289), with the lived experiences within DIOCs requiring deeper unpacking and investigation. This inherent contradiction between increased diversity within organizations, as represented in their employee workforce, and the drive for increased inclusion among such disparate subgroups and cohorts requires a more nuanced examination of factors that impact employee performance and well-being.

Within the EDI (equality, diversity and inclusion) discourse, recent critical discussions have focused on exposing systemic organizational norms that perpetuate inequalities across employee subgroups. Carr (2026, p. 501) found that the “bring your whole self to work” rhetoric within the EDI discourse is problematic since “consent to the terms of inclusion … means that a subject's attributes must not impact others, the organisation or our own productivity and they [the individual subjects] are held responsible for making sure that this happens.” Working in a DIOC, therefore, assumes that one acclimates and enacts appropriate work activities that are welcomed and expected in that culture; “for the individual to repackage themselves as appropriate human capital rather than on accommodations made by the organisation” (Carr, 2026, p. 501).

We challenge the functionalist assumption that inclusive cultures are better for all employees (all-inclusive) by examining whether DIOCs create asymmetric stress outcomes by gender. This critical perspective aligns with scholarship in EDI research that questions whether organizational diversity initiatives achieve substantive change or merely reproduce existing inequalities in new forms (Noon, 2007; Zanoni et al., 2010). As Tatli and Özbilgin (2012) argue, diversity management practices are embedded within broader power relations that shape who benefits and who bears the costs of organizational change. While low stress in dominant groups may signal comfort or assimilation, a lack of stress reduction for marginalized groups may signal the presence of “inequality regimes” (Acker, 2006) – organizational processes that systematically produce and reproduce class, gender and racial inequalities.

Drawing on the literature of emotional labor (Hochschild, 2019) and invisible work (Daniels, 1987), we argue that DIOCs may paradoxically increase demands on female employees through expectations for diversity-related emotional and invisible labor, while simultaneously reducing demands on male employees by easing masculine performance pressures. Using a longitudinal observational design with 1,441 employees who transitioned between organizations, we leverage within-person variation to identify the effect of DIOC exposure on occupational stress levels. We define our independent variable as the exposure to a DIOC, measured via natural language processing (NLP) of employee reviews. Our dependent variable is employee stress, quantified as the proportion of stress-related linguistics used in job reviews, with employee gender (male vs female) moderating this relationship. We examine whether the transition from a baseline culture (Company A) to a destination culture (Company B) interacts with employee gender to produce differential stress outcomes.

In doing so, we make three key contributions to the literature. First, we move beyond a functionalist, managerialist perspective of DIOCs, as expressed by employees within the organization rather than in its public rhetoric, by examining unintended consequences. We examine whether what is marketed as a “resource” for women may function as a mechanism for labor extraction, thereby challenging the business-case assumption that inclusion is a universal benefit. Second, we extend the Job Demands-Resources model (Bakker and Demerouti, 2017) by showing how organizational cultures can simultaneously function as resources for some employees while creating demands for others, depending on the invisible labor expectations they generate. Third, we provide empirical evidence for the “inclusion tax” that female employees pay in DIOCs, namely the additional stress burden of performing uncompensated diversity work that their male colleagues are not expected to undertake.

Organizational culture is a tacit social structure that represents the shared basic assumptions learned by a collective within an organization, in the context of the particular external and internal structures in which it operates (Schein, 2010). It comprises accepted norms of working practices, shared beliefs, values, historical memories and behaviors that underpin the behavior of the organization and its employees (Lim, 1995). Underlying assumptions inherent in organizational cultures refer to the intangible perceptions, thoughts and feelings associated with life and behaviors in that particular organization; as such, organizational culture has been described as the cohesive force or mechanism that pulls an organization together and can stimulate employee performance and commitment (Van den Berg and Wilderom, 2004).

Extensive research has documented the performance benefits of strong organizational cultures (Graham et al., 2017). For example, studies found that half of the interviewed senior executives across 1,348 North American firms cited organizational culture as one of the most critical drivers of their organizations' value and economic output. They also found that 92% of respondents affirmed that an improvement in the firm's organizational culture would increase its value. Relatedly, previous studies have shown that organizational cultures that prioritize gender equality significantly increase organizational innovation capacity, improve brand image, and ultimately enhance financial performance (Cropley and Cropley, 2017), thereby creating a business case for gender diversity and equality in organizations. However, to our knowledge, prior research has not examined whether all employees benefit equally from such cultures.

It is important to distinguish DIOCs from the related but distinct construct of “inclusion climate” (Nishii, 2013; Shore et al., 2011). The two constructs differ in three key respects. First, with respect to level of analysis, inclusion climate is primarily an individual-level perceptual construct that captures the degree to which a specific employee feels included in their immediate work environment. DIOCs, as conceptualized and operationalized in this paper, are an organization-level cultural construct reflecting the collective emphasis on diversity and inclusion values as expressed through the aggregate linguistic output of an organization's workforce. Second, with respect to measurement, inclusion climate is typically assessed using standardized survey instruments that tap individual psychological experiences, whereas our DIOC measure captures the density and valence of diversity-related discourse in organizational language. Third, with respect to theoretical emphasis, inclusion climate scholarship tends to focus on whether individuals feel they belong; DIOC scholarship, as developed in this paper, focuses on the organization-level cultural norms and expectations surrounding diversity and whether these norms and expectations produce equal or unequal well-being outcomes across groups.

Diversity and inclusion-oriented cultures, while promoting values of equity and belonging, create new institutional logics that fundamentally alter workplace demands (Tatli and Özbilgin, 2012). These cultures characterized by an emphasis on compassion, understanding and collective well-being – traits traditionally associated with femininity (Bem, 1974; Heilman and Okimoto, 2007) – should, in theory, benefit female employees by aligning values. According to Bem (1974), masculinity and femininity are distinct constructs that combine and co-exist within each individual (across the male and female binary). Masculinity-associated adjectives include “independent”, “dominant”, “aggressive”, “assertive”, “willing to take risks” and “forceful”, whereas the femininity construct comprises “compassionate”, “affectionate”, “sympathetic” and “understanding”. These adjectives may also be associated with masculine- and feminine-oriented organizational cultures, where behavioral norms correspond with particular perceptions of accepted values and behaviors in different organizations, aligning with the theory of gendered organizations (Acker, 1992). As a result, gender roles are culturally defined behavioral norms associated with males or females within a given social group (Connell, 1987), fundamental for understanding how people behave (Alvesson and Due Billing, 2009).

Therefore, according to conventional wisdom, inclusive organizational cultures (i.e. those inherently associated with femininity) should provide resources that reduce stress for marginalized groups. For example, Bajdo and Dickson (2001) found that in organizational cultures associated with more female values (e.g. high humane orientation, low power distance, high gender equity), employees report higher percentages of female employees in management positions.

In support, Burnford (2019) found that the challenges female employees face are likely due to gendered organizational cultures that base their organizational norms on masculine preferences and characteristics. Existing literature on gender and organizational culture shows explicitly that female employees can face cognitive dissonance within hegemonic masculine work cultures and patriarchal institutions (Orgad, 2019), which prioritize masculine-focused behaviors such as competitiveness over collaborative working (O'Brien, 2024). Such cultures may push female employees out of their organization, due to discriminatory work practices that do not align with female values (Metz, 2011; O'Brien, 2024). According to this perspective, females are perceived as being “more communal and more empathetic than men” (Badura et al., 2018). On the other hand, males have traditionally been considered more agentic than females, professing that “gender's association with agentic and communal traits has been well established [with] task-oriented behaviors […] more strongly associated with agentic traits than communal traits”. It stands to reason that an organizational culture that prioritizes diversity and inclusion, by its very nature, should benefit all employees, particularly female employees. That is because feminine-oriented adjectives, including “compassionate”, “sympathetic” and “understanding”, are more likely to be espoused in strong DIOCs.

Individuals prefer working for organizations with shared values, as a “values-misfit environment tends to lead to stress” (p. 103773; Terpstra-Tong et al., 2022). In line with the importance of organizations focusing on diversity and inclusion, Efron (2022) found that “42% of U.S. employees say a diverse and inclusive organization is important” because such cultures are about “belonging […], being respected, welcomed and valued”. However, this conventional view overlooks a critical mechanism: the invisible and emotional labor that DIOCs demand. Moreover, this functionalist orientation tends to assume that inclusive cultures operate similarly across social groups and that gains in well-being reflect progress toward equality.

Seemingly neutral organizational practices often create gendered outcomes through hidden work requirements. In DIOCs, these requirements are likely to manifest as what we term the “inclusion tax”. We conceptualize the “inclusion tax” as a dual burden borne disproportionately by female employees: “organizational housework” (the tangible administrative and supportive tasks of EDI such as serving on diversity committees, mentoring underrepresented employees, organizing inclusion events) and “identity labor” (the emotional energy required to navigate, mediate and represent marginalized identities in diversity-conscious spaces) to make others feel welcomed and valued (Humphrey et al., 2008).

Unlike emotional labor, which refers to managing one's own affective displays in customer-facing or client-oriented roles (Hochschild, 2019), or the invisible domestic and care work documented by Daniels (1987), the inclusion tax operates specifically within professional organizational settings and is generated by formal DEI commitments themselves. Its distinctiveness lies in who bears the cost: it falls disproportionately on the very groups those commitments are designed to empower, creating a structural paradox within inclusive organizational cultures. Critically, this labor is not distributed equally. Research on organizational citizenship behaviors reveals that women, particularly in diversity-conscious environments, face heightened expectations to engage in “organizational housework”. In DIOCs, this housework likely includes diversity championship, a form of tempered radicalism that requires significant emotional energy to navigate (Meyerson and Scully, 1995). Female employees in these cultures may feel obligated – either through explicit requests or implicit expectations – to serve as diversity champions within their teams and organization, participate in and lead committees, and mentor more junior organizational members. As a result, women in DIOCs may experience increased demands (JD-R; Bakker and Demerouti, 2017) in the form of increased pressure and stress, due to increased emotional labor (Hochschild, 2019) and invisible labor (Daniels, 1987). They may also experience heightened expectations and pressure to conform to the norms associated with that organizational culture (Terpstra-Tong et al., 2024). With more invisible work and other (non-performance-related) work being conducted by female employees in such organizational cultures, male employees would not have the same additional emotional load and therefore experience lower stress levels or lower demands (Bakker and Demerouti, 2007, 2017).

Hence, while conventional wisdom, rooted in person-organization fit theory and value congruence research (Kristof-Brown et al., 2005), would suggest that female employees should experience reduced stress in diversity-oriented cultures due to improved value alignment, this perspective assumes that cultures emphasizing traditionally feminine values of inclusion, compassion and collaboration would naturally benefit women by creating more hospitable work environments. We challenge this conventional wisdom by proposing that the hidden labor demands of DIOCs can inadvertently and disproportionately burden female employees with emotional and invisible labor, thereby offsetting any stress-reduction benefits from value alignment. Meanwhile, male employees benefit from a more collaborative and less competitive environment without bearing the same diversity labor burden, creating an occupational health paradox where initiatives designed to support women's well-being may actually maintain or exacerbate gender-based stress disparities. We hypothesize the following:

We visualize these hypothesized relationships in Figure 1.

We measure stress using job reviews on Glassdoor (https://glassdoor.com). Glassdoor is one of the world's largest job search engines and job review websites, with over 90 million reviews of 1.5 million employers. The data provided for this study exclusively list job reviews from employees in the United States of America (USA), most of which were submitted between January 2015 and September 2020. Glassdoor provided this dataset for the sole purpose of academic research and analysis. Recent organizational academic work has utilized Glassdoor data to study work-related phenomena (Canning et al., 2020; Corritore et al., 2020). Glassdoor data are considered one of the most trustworthy sources of information available, surpassing corporate websites and other related corporate documents (Lakin, 2015). By utilizing employee-generated reviews rather than official corporate rhetoric, our approach captures the “lived experience” of the culture rather than its aspirational marketing.

The provided Glassdoor dataset was merged with organizational culture data from the Culture 500 project, which inferred organizational culture scores using linguistic analytics. This methodology enables scholars to extract linguistic themes and insights from available textual data by exploiting linguistic elements such as syntax, semantics and lexicon. Previous examples include the use of linguistic markers to monitor psychosocial health over time (Gruda and Hasan, 2019; Gruda and Ojo, 2022). Thus, the organizational culture data used in this research consist of employees' self-reported attributions of specific characteristics to their respective organizations' cultures, rather than references to a particular organizational culture through an organization's public rhetoric. The supporting materials file includes descriptions of each of the nine organizational culture types identified by the Culture 500 project. Specifically, for this research, the diversity culture is described by the Culture 500 project as exemplified when an organization “promotes a diverse and inclusive workplace where no one is disadvantaged because of their gender, race, ethnicity, sexual orientation, religion, or nationality.” It is an environment that values “inclusion”, “everyone is welcome” and “celebrates differences”.

To examine employees who switched cultures, we included only observations from those who provided two job reviews. Furthermore, we only considered job reviews (for both company A and company B) with a confidence score of 1 (i.e. 100%). The confidence score reflects Glassdoor's certainty that individuals actually work(ed) in the roles and companies they have indicated, minimizing misclassification and enhancing data validity. This step resulted in a sample of 6,211 participants. However, due to missing data for gender and other essential controls, such as age, education and overall company rating, the sample was further reduced to 3,578 participants. Of these, 1,121 had either spent less than one year in each company (company A and company B) or had failed to indicate the time of employment at each firm. We included only employees who had been with their respective firms for more than one year.

We also excluded observations in which employees switched from one contractual arrangement to another (n = 910). Transitioning from an internship to a full-time role, for example, is likely to involve different responsibilities, which could affect employees' stress levels. Similarly, transitioning from a full-time position at Company A to a freelance or fixed-term contract role at Company B introduces uncertainty that may further increase stress. Since such changes could introduce variability (i.e. noise) into the data, we focused only on employees who remained in the same contractual arrangement, thereby maintaining consistent employment type status across both companies.

Furthermore, for the present analysis, we only considered data up to (and excluding) 2020, due to the likely (exogenous) influence of the SARS-CoV-2 pandemic on employees' stress levels. Finally, five employees indicated they were over 100 years old when they submitted their reviews. As it is improbable that participants of that age were a) still working and b) posting job reviews on Glassdoor, we dropped these observations as well. These steps yielded a final sample of 1,441 employees across 425 organizations in 20 distinct sectors. A list of the largest sectors, along with examples of respective firms in each industry, is provided in Table 1.

The authors acknowledge the use of AI-assisted technology in the preparation of this manuscript. Specifically, Claude AI (Anthropic) 4.1 Opus was utilized to refine sentence structure, enhance clarity of expression and ensure consistency in academic tone throughout the manuscript. All substantive content, theoretical arguments, critical analysis and conclusions are the original work of the authors. The authors reviewed all AI suggestions for accuracy, relevance and appropriateness. The interpretation and application of these sources to the paper's argument remain entirely the authors' responsibility. The authors take full responsibility for the content, conclusions and any errors or omissions in this work.

Employee stress. Linguistic inquiry and word count (LIWC) is a computational tool that analyzes language by classifying words into psychological categories, offering insights into the emotional and cognitive components of text. LIWC enables researchers to assess psychological states based on the frequency and usage of words. In this study, we used LIWC to analyze the linguistic content of job reviews (positive and negative aspects of working at a particular company), focusing on identifying stress-related language. We applied the Stress Dictionary developed by Wang et al. (2016), an extension of the standard LIWC dictionaries, to detect stress-related language. This dictionary includes an extensive range of words commonly associated with stress, such as “agony,” “anxiety,” “grief,” “fail,” “frustrate,” “hate” and “rage”. By leveraging this specialized lexicon, we were able to capture nuanced expressions of stress within the text. The stress score is calculated as the ratio of stress-related words to the total word count of the review (Stress Words/Total Words), expressed as a percentage (recoded to a value of 0–1 for the fractional logit model). We distinguish between Stress A (the LIWC-derived stress score from the job review for the origin company, Company A) and Stress B (the LIWC-derived stress score from the review for the destination company, Company B). Stress A serves as the within-person baseline covariate; Stress B is the outcome variable.

Organizational culture. While over 85% of Fortune 500 organizations provide statements outlining corporate values and information related to organizational culture on their corporate websites or other documents (Guiso et al., 2015), publicly communicated organizational values and norms do not necessarily align with actual organizational cultures (Sull et al., 2019). To measure an organization's DIOC in a sophisticated manner, we relied on the Culture 500 project's work (Sull et al., 2019). Culture 500 developed an online tool to explore organizational cultural insights among organizations employing 34 million people in the United States (Sull et al., 2020). Using NLP, Culture 500 analyzed a dataset of 1.2 million employee reviews from Glassdoor (a much larger dataset than that used in this study). It categorized review text into 90 culture-related topics, yielding nine cultural dimensions, one of which was diversity and inclusion. For each cultural dimension, both incidence (i.e. frequency of diversity-related linguistics mentioned in any given review; 0–1 range) and sentiment (i.e. reviews discussing diversity in favorable terms; 0–1 range) are measured. To derive a single factor reflecting the importance of a cultural value within firms for our analyses, we multiply the incidence and sentiment scores to obtain a final DIOC score for each company. We used only the “Diversity and Inclusion” dimension in this study.

Importantly, this measure captures the extent to which diversity and inclusion values are present in the discourse and lived experience of employees, rather than in officially sanctioned policies or HR frameworks. It thus reflects the perceived and experienced organizational culture, which is theoretically more proximal to employee stress outcomes than formal policy documents.

Gender. Employee gender (1 = female, 2 = male) was obtained from the Glassdoor dataset, in which respondents self-identified as male or female. Our regression models automatically excluded observations without the gender variable. We acknowledge that this binary classification is a limitation of the data and obscures the experiences of non-binary employees.

Overall company rating. Company status may appeal to some employees to the extent that their perception of the company's status influences their decision to switch employers. To account for this possible effect, we included an “overall company rating” (i.e. the overall rating provided by the respective employees for the company they move to, company B; self-report scores on a 1–5 Likert scale, where 1 indicates the most negative overall assessment and 5 the most positive) in our analysis.

Word count. Word count refers to the total number of words in each Glassdoor job review. Word count does not enter the main regression as a covariate, because our dependent variable (linguistic stress) is itself computed as a proportion of stress words to total words; including raw word count as a predictor would introduce ratio-variable bias. Instead, we use the natural logarithm of word count as a probability weight in a robustness check, prioritizing more informationally dense reviews (see Robustness Check section below).

Time of review. To account for time-specific effects, we included the time of review submission in our model, doing so allows us to control for specific organizational effects associated with a particular period. For example, an organization may have had to lay off a significant portion of its workforce in a given year, which could skew reviews for that year. Additionally, employees frequently move between organizations, enabling them to provide multiple reviews of the job roles they have held. Because our model is multi-level and longitudinal, it accounts for instances in which the same individual provides reviews for different job roles across different organizations over time. To do so accurately, however, we included time (in years) as a categorical covariate (fixed effect) to account for temporal trends and economic cycles.

Demographics. We also included age (self-reported, in years) and level of education (1 = High School, 2 = Associate's, 3 = Bachelor's, 4 = Master's, 5 = MBA, MD, or JD, 6 = PhD) in our analysis.

To test our hypotheses, we use a longitudinal, transition-based design with two observations per individual, capturing stress levels at Company A at time one and at Company B at time two. While our data structure captures change within the same individuals across two time points, we explicitly model this transition using a Lagged Dependent Variable (LDV) approach. Including the baseline stress level at the initial organization as a covariate effectively models residualized change. This approach allows us to isolate the specific effect of the destination organization's culture on subsequent stress while accounting for the individual's prior psychological state.

We selected an LDV specification over a person-level fixed-effects model for several critical reasons. First, a standard fixed-effects model removes all time-invariant variation, which would preclude including gender, a stable demographic characteristic central to our moderation hypothesis. Second, our research focuses on the impact of moving from one specific cultural environment to another. To account for baseline DIOC, following Edwards (2002), we specified a three-way interaction term comprising gender, DIOC at Company A and DIOC at Company B, rather than using difference scores (Δ), which often exhibit reduced reliability. This allowed us to a) isolate the effects of DIOC changes on employee stress and b) assess how the combination of an employee's gender and the change in DIOC between companies affected their stress levels at their new organization (and culture).

Finally, given the hierarchical structure of our data, where individual reviews (Level 1) are nested within companies (Level 2), observations are not independent (Rabe-Hesketh and Skrondal, 2008). Multiple employees may originate from or move to the same organization, creating clustering effects. In such cases, a multilevel specification is appropriate and preferred to account for potential non-independence among employees nested within destination companies. Therefore, we treat individual employee reviews as nested within the destination Company B. This specification is theoretically motivated: because our dependent variable (Stress B) captures each employee's experience at their destination organization, it is shared membership in destination companies that generates non-independence in the outcome. Furthermore, the primary cultural predictor of theoretical interest – DIOC at Company B – is itself a destination-company-level construct, ensuring that the random-effect structure is aligned with the theoretically relevant contextual unit; Stress A and DIOC at Company A are controls for baseline stress and origin-company culture, respectively, substantially mitigating – though not formally eliminating – confounding from origin-company characteristics. We employed a two-level fractional logit model with robust standard errors and random company-level intercepts. This estimator is appropriate for bounded outcome variables, such as our dependent variable, employee stress and avoids the bias inherent in OLS regression for such data. All analyses were conducted using Stata 19.0. To justify the multilevel framework, we first estimated a null model without predictors (log-likelihood = −995.02; N = 1,441; K = 425 clusters). The between-company variance was small and non-significant (var(u0) = 0.03; LR test p = 0.25), yielding an intraclass correlation coefficient (ICC) of approximately 0.95%. While an ICC of this magnitude does not strictly require a multilevel specification, we retain the two-level structure because it formally accounts for the non-independence arising from the nested data structure and yields more precise standard error estimates compared to ordinary least squares regression under unbalanced cluster sizes (Snijders and Bosker, 2012; Rabe-Hesketh and Skrondal, 2008). This is also consistent with our theoretical expectation that cultural effects operate primarily through the three-way interaction rather than as main company-level effects (Snijders and Bosker, 2012).

Pairwise correlations and descriptive statistics are provided in Table 2.

We found no significant differences in stress between female and male employees, neither at their original company (t(1,439) = −0.46, p = 0.65) nor at the company they moved to (t(1,439) = −0.06, p = 0.96).

The interaction between gender and DIOC at Company A, as well as DIOC at Company B, significantly predicted stress scores in job reviews for Company B (Table 3; b = 25.81, SE = 10.90, z = 2.37, p = 0.018).

To better understand this interaction, we plot it accordingly (Figure 2). We use the median (50th percentile) for organizational culture diversity at Company A (the company from which participants come, also known as the diversity baseline), as well as 5th, 50th and 95th percentile diversity scores to showcase the change in effect when participants move to a less DIOC, similar and more DIOC (Company B).

We found no significant effect for female employees moving to a more DIOC in our analysis (χ²(1) = 0.01, p > 0.10) nor a significant change in stress levels for female employees moving to a less DIOC (χ²(1) = 0.01, p > 0.10), providing support for H1a.

Conversely, for male employees, moving from a median diversity culture to a more DIOC was associated with significantly decreased stress (χ²(1) = 6.90, p = 0.009), while moving to a less DIOC was associated with increased male employee stress (χ²(1) = 6.76, p = 0.009). Differences between male and female employees were also observed, and they were strongest (χ²(1) = 4.92, p = 0.027) when employees moved from a very low DIOC (e.g. 5th percentile) to a much stronger DIOC (e.g. 95th percentile), providing support for H1b. Overall, male employees appeared to benefit from transitioning to more DIOCs, experiencing a stress reduction.

Robustness check. Job demands such as increased workloads, time pressures and a lack of job autonomy can increase employee stress (Hakanen et al., 2005), while the presence of job resources, such as a good work-life balance, career opportunities and good benefits, can empower employees and allow them to fulfill motivational needs such as autonomy (Albrecht et al., 2018), alleviating stress as a result. Although we were unable to test the role of specific job demands due to the lack of this information in the provided dataset, we can control for job resources. Employees in our dataset provided ratings (all on a scale of 1 (lowest) to 5 (highest)) for several job resource proxies, including compensation/benefits, career opportunities and work–life balance. We therefore replicated our main model by adding these additional control variables (for Company A and Company B, respectively). The three-way interaction remained essentially unchanged (b = 24.85, SE = 11.65, z = 2.13, p = 0.033), and significance levels were stable (i.e. coefficient changes were negligible), confirming the validity of our main model.

Finally, to ensure that our results were not driven by differences in the reliability of short vs long reviews, we conducted a robustness check using probability weights based on the natural log of the review word count. This approach acknowledges that longer reviews yield more precise and reliable estimates of an individual's psychological state. Weighing the observations by the log-transformed word count allows us to prioritize information-rich reviews in the estimation process while ensuring that exceptionally long texts do not disproportionately skew the results. The three-way interaction remained significant and stable under this specification (b = 34.91, SE = 13.01, z = 2.68, p = 0.007).

While research on inclusion has expanded rapidly across organizational studies, occupational health and HRM, positioning inclusive organizational cultures as universally beneficial, associated with enhanced well-being, engagement and performance, is problematic. Our study shows that DIOCs are not gender-neutral or pro-women (or, arguably, pro-other minorities with complex, layered intersectionalities), but consistently reproduce inequalities that impact more negatively on the very subgroup/population they are, rhetorically, supposed to promote and protect. Systemic biases that undermine minorities and extend greater challenges to minorities to perform in a system designed traditionally for privileged male employees persist, rendering DIOCs not as attractive to minorities as rhetoric would infer. While employees themselves may rate organizations as high on DIOC with positive characteristics associated with DIOCs (Culture 500 study), the pressure to conform to “Stepford Wives” perfection and contentment within such DIOCs requires deeper analysis.

Our findings reveal a troubling occupational health paradox within organizations' diversity and inclusion efforts. While male employees who move to stronger DIOCs report significantly reduced stress, female employees experience no reduction in stress, despite moving to supposedly more supportive environments.

Our findings complicate the narrative that employees experience less stress when their values align with organizational culture (Groysberg et al., 2018), suggesting that DIOCs function differently across groups. Several mechanisms may explain why male employees benefit while female employees do not. First, male employees in DIOCs may feel less pressure to conform to traditional masculine norms, thereby reducing competition-based stress without taking on new responsibilities. They can express emotions more freely and collaborate without fear of appearing weak, reflecting the benefits of inclusive cultures without associated costs. The observed stress reduction for male employees suggests that DIOCs may function as a “psychological safety buffer,” reducing the demand for competitive masculine performance while failing to redistribute the labor required to sustain that safety.

This asymmetry is consistent with the theory of gendered organizations (Acker, 1990; Connell, 1987; Sayce and Acker, 2012): even in DIOCs, the underlying organizational logic remains gendered in important ways, with the norms, structures and informal expectations of the workplace continuing to assign the maintenance of diversity and inclusion culture – the relational and emotional labor of mentoring, advocacy and coalition-building – primarily to women, treating it as a natural extension of feminine relational labor rather than as formally assigned organizational work (Daniels, 1987; O'Brien, 2024). Men in DIOCs, by contrast, benefit from a cultural softening of traditional masculine performance demands without incurring additional formal or informal responsibilities, so that DIOC exposure functions asymmetrically: as a job resource for men and as an additional demand for women. Conversely, female employees in DIOCs likely face heightened expectations and demands through an “inclusion tax” – the uncompensated emotional and invisible labor of performing “organizational housework” and promoting diversity initiatives.

It is important to note that the “inclusion tax” represents a theoretically grounded interpretation of our results rather than a directly observed causal mechanism: our data robustly demonstrate asymmetric stress outcomes by gender, but the proposed mechanism (i.e. female employees bear disproportionate diversity-related labor) is inferred from theory rather than directly measured in the present dataset. These expectations may manifest both explicitly (through committee appointments and mentoring requests) and implicitly (through internalized responsibility to champion diversity). The irony is that by creating opportunities for female employees to be visible and involved, DIOCs may unintentionally increase their workload while decreasing stress solely for their male colleagues.

These differential outcomes raise a fundamental question for EDI scholarship: does low stress in DIOCs indicate genuine inclusion, or does it reflect assimilation into organizational norms that remain fundamentally unchanged? For male employees, reduced stress may suggest that DIOCs make traditional organizational life more comfortable without requiring any substantive behavioral or attitudinal change. The organization becomes more “human-friendly” for those who already belong, while the work of creating and maintaining this friendliness falls on others. This distinction between comfort and inclusion is critical: true inclusion would require not only that some employees feel less stressed but also that the organization genuinely accommodates diverse ways of being without imposing additional labor on marginalized groups. Our findings suggest that many organizations may be achieving the former while failing at the latter – creating what might be termed “comfortable exclusion” for dominant groups and “exhausting inclusion” for others. For women, the lack of stress reduction suggests that DIOCs may be “inequality regimes” (Acker, 2006) in disguise, where the labor of inclusion is offloaded onto the very groups the culture claims to serve. Overall, the findings underscore that women encounter distinct structural disadvantage with adverse well-being effects in DIOCs, and that a systemic dismantling of cultural norms that reinforce conformity and obedience to male-originated systemic norms and ways of behaving in organizations is required to build work environments that are malleable to the needs and behaviors of diverse employees, including women and other minorities under-represented in decision-making roles within organizations.

The results of this study also question the JD-R conceptualization of “resources” as buffers against the demands placed on employees and as benefits to employees' well-being outcomes (Bakker and Demerouti, 2007, 2017). Female employees working in an environment that promotes diversity- and inclusion-oriented values and norms, and presumably expects them to incorporate these values into their core, are not buffered from organizational demands; their stress levels remain unchanged when they transition to a more DIOC environment. Indeed, this finding aligns with recent critiques (Bal et al., 2025) that the JD-R model inadequately accounts for employee characteristics, such as gender, age and socioeconomic background. This is a significant contribution: organizational cultures can simultaneously function as resources for some employees while creating demands for others. This is a nuance the traditional JD-R framework overlooks.

Finally, our findings should be interpreted within essential boundaries. Effects may be most potent in organizations where diversity initiatives are new or contested, creating pressure on female employees to prove their value. In organizations with mature, institutionalized diversity cultures, the burden might be more equitably distributed. The industry context is likely important as well, as male-dominated sectors may create particularly intense labor demands for diversity and inclusion among women. We encourage future research to examine specific diversity practices that create differential stress burdens, use time-use data to document invisible diversity labor and track how stress effects evolve as diversity initiatives mature. We also encourage studies that seek to unpack the complexity of competing factors impacting inclusion and well-being, such as Dheer et al.’s (2026) international, multi-level study examining the relationships among trust in top management, employee psychological safety and organizational culture. Rather than reducing parameters to a purely functionalist perspective, a broader, more nuanced critical interrogation of causes and effects should be promoted to better uncover obstacles to improving universal well-being at work.

Our findings suggest that simply “having” a DIOC is insufficient and may even be counterproductive unless paired with structural accountability. This redistribution creates a hidden form of inequality where the emotional and psychological burden of maintaining inclusive cultures falls disproportionately on those these cultures purport to support. The most immediate implication concerns the formal recognition of labor diversity. Currently, much of the work required to maintain inclusive cultures remains invisible in job descriptions, performance evaluations and compensation structures (McKinsey & Company and LeanIn.Org, 2021). Organizations should explicitly acknowledge their diversity-related responsibilities, and HR leaders are positioned to drive this change. This begins with auditing the “invisible labor” of inclusion. If serving on a diversity committee requires five hours per week, this time commitment should be explicitly recognized, and other responsibilities adjusted accordingly. Without such formal recognition, diversity work becomes an add-on burden that (female) employees are expected to absorb within existing workloads.

Our findings suggest that female employees disproportionately bear the burden of diversity labor, experiencing no stress reduction even in supposedly supportive environments. To address this inequity, HR must ensure equitable distribution of this work. This involves implementing systematic approaches, such as rotating committee assignments or developing sponsorship programs that hold senior leaders of all backgrounds accountable for diversity and inclusion outcomes. One example is “diversity sponsorship” programs, in which senior leaders, regardless of their demographic characteristics, are held responsible for specific diversity outcomes and actively participate in efforts to promote inclusion.

To dismantle the structural inequality inherent in this “inclusion tax,” compensation structures must evolve. If diversity work is valuable, it must be visibly tied to career progression, bonus allocations and promotion decisions. This moves D&I labor from a “nice-to-have” to a formally compensated part of an employee's role. Currently, diversity work often falls into the category of “organizational citizenship behavior”: appreciated but not rewarded. This must change if organizations are truly committed to equitable stress distribution.

Our findings also have implications for governance and policy. Regulatory bodies and industry associations should consider developing standards for measuring and reporting the distribution of diversity-related labor within organizations. Just as gender pay gap reporting has become mandatory in many jurisdictions, “inclusion labor audits” could reveal whether the burden of maintaining diverse workplaces falls equitably across demographic groups. Such transparency mechanisms would shift accountability from individual employees to organizational structures, aligning with calls in the EDI literature for moving beyond individual-level interventions toward systemic change (Kalev et al., 2006). Professional bodies could also incorporate diversity labor distribution into organizational benchmarking and certification processes, creating external incentives for equitable practice.

Organizations should also systematically audit who performs diversity-related work – including committee membership, mentoring relationships, cultural programming and representational duties – and actively redistribute this labor across demographic groups. Critically, diversity responsibilities should be formally assigned in job descriptions and performance agreements, with corresponding adjustments to other workload expectations. This moves inclusion labor from a voluntary “nice to have” to a formally managed organizational resource, reducing the likelihood that it defaults to those with the least positional power to decline it.

Relatedly, senior leaders (regardless of gender, race or background) should be held personally accountable for specific and measurable EDI outcomes through performance reviews, bonus criteria and promotion decisions. Accountability at the top reduces the extent to which inclusion labor cascades downward, disproportionately falling on those with the least positional power to decline it. This structure ensures that EDI initiatives are driven by institutional responsibility rather than individual sacrifice.

Several limitations warrant consideration. First, we rely solely on employee reviews, rather than official corporate documents, such as value statements from company websites. While it could be argued that including official corporate literature in our analyses would provide richer linguistic data, we believe that adding such “corporate” data may dilute our findings. To illustrate, while a company may publicly state that “here we value diversity in people and thought. It's only by being able to recruit from a diverse pool of talent that we'll be able to maintain a truly outstanding workforce”, this does not make it so (quote derived from Enron's annual report in 1998). Hence, official corporate values, as often displayed on corporate websites, are not typically associated with the actual “lived” organizational culture and values. Indeed, the Culture 500 project team (Sull et al., 2020) examined the publicly listed corporate values of almost 700 companies and compared this information to the Culture 500 cultural dimensions dataset. The respective authors found only a low correlation between public corporate values and values expressed and assessed based on employees' job reviews on Glassdoor. Nevertheless, we do acknowledge that employees who write reviews may differ systematically from those who do not. While our within-person design partially addresses this issue by using the same individuals across companies, we cannot rule out the possibility that review-writing behavior itself changes in response to organizational transitions.

Second, our stress measure relies on linguistic analysis of job review text using LIWC dictionaries. While LIWC has been validated across numerous contexts, using word frequencies as a proxy for psychological states has inherent limitations. The stress dictionary may not capture all manifestations of occupational stress, particularly those expressed through euphemism, professional language, or cultural idioms. Additionally, our measure cannot distinguish between acute and chronic stress, nor can it capture stress that employees choose not to express in public reviews. Future research should triangulate our findings using validated psychometric stress measures, physiological indicators or health outcomes data.

Third, our inability to observe the actual allocation of diversity-related work limits our ability to establish mechanisms definitively. While our theoretical framework suggests that female employees bear a disproportionate burden of diversity labor, we cannot directly observe committee assignments, mentoring relationships or time spent on inclusion activities. Future research should collect time-use data or conduct ethnographic observations to document the invisible labor our theory proposes.

Fourth, as noted in the measures section, the binary classification of gender in our dataset limits our ability to capture the experiences of non-binary and gender-diverse employees, who may face distinct and potentially higher inclusion taxes. Non-binary employees may face unique stressors in diversity-oriented cultures that our analysis cannot capture. Beyond the binary gender limitation, our data does not permit a full intersectional analysis. It is highly probable that the “inclusion tax” is regressive, with the highest stress burdens falling on women of color or LGBTQ + employees, whose labor is often even more invisible and undervalued within organizational structures. Additionally, we cannot examine intersectional effects, namely how race, sexual orientation or other identities interact with gender to shape stress outcomes in DIOCs. These are avenues for future research.

A final limitation concerns the nature of organizational transitions in our dataset. Our data do not permit us to distinguish between voluntary and involuntary job changes. Research suggests that women are more likely than men to exit organizations for push factors such as non-inclusive cultures (Metz, 2011), whereas men may transition more often for pull factors such as advancement opportunities. If such gender differences in mobility patterns characterize our sample, this could independently influence baseline stress levels captured by Stress A. Our lagged dependent variable design partially mitigates this concern; future research using administrative data capturing reason for departure would strengthen causal inference.

This paper responds to recent calls questioning the validity of diversity and inclusion initiatives across organizations. Our analysis of 1,441 employees who transitioned between organizations reveals an uncomfortable truth: DIOCs are associated with reduced stress for male employees but provide no stress reduction benefits for female employees. This asymmetric outcome suggests that the hidden labor required to maintain inclusive cultures creates a new form of workplace inequality, one measured not in traditional metrics, such as pay gaps or promotion rates, but in the differential distribution of emotional burden and occupational stress. The portrayal of DIOCs as equitable environments where all employees benefit equally – what Yarrow and Johnston (2023) term “peacocking” – is not realized when we examine actual occupational stress outcomes. Instead, these cultures appear to create a paradox where those already advantaged experience improvements in well-being. At the same time, those meant to be supported maintain their stress levels despite supposedly more inclusive environments. These findings demand that we move beyond simplistic pro- or anti-diversity positions. The problem lies not with inclusion goals but with implementation approaches that inadvertently burden those they intend to help. A truly inclusive organization is not one that merely declares inclusive values but one that actively monitors and addresses the hidden costs of upholding them. The “inclusion tax” we identify represents a form of structural inequality that diversity discourse often obscures: the systematic extraction of emotional and organizational labor from marginalized groups under the guise of empowerment. Addressing this requires not only better HR practices but also fundamental shifts in how organizations conceptualize, measure and distribute the work of inclusion.

Our findings emphasize the need to move beyond the rhetoric of inclusion and to operationalize structurally inclusive practices that do not further penalize underrepresented workforce subgroups (in our focus, women). These findings carry direct policy implications. Across contemporary labor markets, DIOCs are increasingly prevalent across labor markets, and if they consistently reproduce the pattern we document – reducing stress for men while leaving it unchanged for women – then gender inequality in occupational health will persist even as organizational investment in EDI reaches record levels. This calls on policymakers and institutional funders of DEI programs to move beyond auditing the “presence” of inclusive cultures towards evaluating their distributional consequences: not merely whether an organization has a DIOC, but whether that culture reduces inequality in the occupational experience of all employee subgroups. To close, we cite Carr (2026, p. 502), “If inclusion is defined by conformity to corporate norms, it risks marginalizing those whose identities do not fit the ideal. When DEI initiatives focus too heavily on ‘fit’ and ‘value’, they may exclude individuals perceived as non-conforming. This raises ethical concerns about the authenticity of corporate DEI efforts and whether they perpetuate or challenge inequality.”