Women CEOs in Mexico: gendered local/global divide and the diversity management discourse
Bibliographic record
Abstract
Purpose The purpose of this study is to add to the existing research on critical perspectives on diversity management (DM). Specifically, this study examines the narratives of women chief executive officers (CEOs) from different countries of origin to understand how they enact the DM discourse by drawing on their past and present experiences at US multinational corporations (MNCs) located in Mexico. Design/methodology/approach This study, based on six open-ended interviews with local and expatriate women CEOs who work in MNCs situated in Mexico, used a sensemaking approach to analyze their narratives. The theoretical foundation of the study is based on decolonial feminist theory, which is used to analyze the hierarchical binary between Anglo-Saxon/European woman and the Mexican/Latin American woman with respect to the discourse of DM. Findings This study found that the dominant discourse used by women CEOs, expats and nationals was a business case for diversity. Female CEOs represent MNCs in favorable terms, compared to those of local companies, despite the nuances in the antagonistic representations in their narratives. This study also found that the women CEOs’ narratives perpetuated a discourse of “otherness” that created a hierarchy between Anglo-Saxons (US/MNCs’ culture) and Latin Americans (Mexican/local companies’ culture). Originality/value This study contributes to critical studies on DM by analyzing diverse forms of power involving gender, race/ethnicity and organizational hierarchy. The use of decolonial feminist theory to examine MNCs is a novel approach to understanding women’s identities and the power differences between local/foreign contexts and global/local businesses. This study also discusses the implications of its findings for women in business careers and concludes with a call for more research within the global South (Latin America).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".