This study employs natural language processing (NLP) to examine how gender is framed within a corpus of business and management articles published by Emerald.
This study employs NLP to analyze the epistemic orientations of gender research in high-impact business and management journals. Methods such as n-gram analysis and Latent Dirichlet Allocation (LDA) were used on 168 Emerald Publishing articles (2023–2024).
We identified a high thematic concentration, since 88% of the articles focus on corporate governance and women's leadership. This concentration reveals a narrowing of gender discourse aligned with neoliberal values (Fraser, 2013), privileging quantifiable, market-based metrics over systemic inequality and intersectionality (Crenshaw, 1991). Moreover, terms such as “non-binary” and “transgender” were virtually absent from the corpus, highlighting a persistent cisnormativity (Ansara, 2016; Keyes, 2018) and the marginalization of gender-diverse identities. NLP methods, while powerful, can both surface and obscure structural biases.
This study has limitations that also represent opportunities for future research. The corpus was limited to 168 articles from a single publisher (Emerald) during 2023–2024, which may affect the generalizability of the findings. While Emerald is a leading publisher in business and management, future studies could expand the analysis to include other major publishers (e.g. Elsevier, Springer and Wiley) and a broader temporal range to examine the evolution of gender discourse over time.
The findings have urgent implications for academic publishers, journal editors and business schools. The near-total absence of non-binary and transgender topics in high-impact business journals signals a systemic failure to represent gender diversity in organizational scholarship. We recommend that journals actively solicit and support research on under-represented gender identities and experiences, and revise submission guidelines to encourage intersectional and critical perspectives.
This study reveals how the systematic exclusion of non-binary, transgender and intersectional perspectives in business research perpetuates structural cisnormativity beyond academia. When high-impact journals consistently frame gender through binary, corporate-centric lenses (e.g. “female director” and “board diversity”), they legitimize a narrow understanding of gender that influences organizational policies, diversity training and leadership development programs worldwide. This not only erases gender-diverse identities from professional discourse but also tacitly endorses a neoliberal model of equality that prioritizes representation over justice and metrics over lived experience. This research implies that transforming business discourse is a social justice imperative. By critiquing and expanding the epistemic foundations of gender knowledge in business, we can contribute to more inclusive economies where organizational practices recognize the full spectrum of gender identity and experience, and where equality is measured not only by who reaches the boardroom, but by whose existence is acknowledged, valued, and protected.
This study offers three key original contributions to the fields of gender studies, critical management, and computational social science: 1. Methodological-theoretical innovation: We introduce a critical feminist NLP framework that moves beyond technical text mining to expose how algorithmic methods can both reveal and reproduce epistemic biases. Unlike most computational studies that treat NLP as a neutral tool, we demonstrate how LDA and n-gram analysis – when paired with feminist epistemology – can uncover not only what is present in gender discourse, but more importantly, what is systematically absent. 2. Empirical discovery of cisnormativity in business research: We provide the first large-scale computational evidence of the near-total erasure of non-binary and transgender identities in high-impact business literature. The absence of terms like “non-binary” and “transgender” (0.02% occurrence rate) in a corpus ostensibly about gender reveals a profound cisnormativity that has previously been discussed theoretically but not quantitatively demonstrated. 3. Critical analysis of neoliberal domestication: We identify and measure what we term the “thematic crystallization” of gender research around corporate governance topics (88% of corpus), providing empirical validation to feminist critiques about the “academic domestication” of gender discourse. Our findings show how gender equality has been narrowed to market-compatible metrics like board diversity, while marginalizing systemic issues like care work, intersectionality and labor precarity. The value of this research lies in its ability to bridge computational rigor with critical theory, offering both a new methodology for feminist discourse analysis and a compelling evidence base for challenging the ideological boundaries of gender knowledge in business and management studies.
