Narratives of workplace resistance: Reframing Saudi women in leadership
Bibliographic record
Abstract
Despite considerable social, economic, and organizational advancements that Saudi women have achieved in the past two decades, research on Saudi women in leadership continues to focus on the structural, organizational, and societal challenges the women face. Often missing from analyses are the micro ways in which the women resist and negotiate with/against organizational challenges. Using a postcolonial feminist lens, we asked: how do Saudi women leaders resist power in the workplace? This question was posed to reinsert the value of Saudi women within organizational narratives, generate deeper understanding of a marginalized group of women, and understand resistance as located within socio-political-ethical structures. Our contributions are threefold: (1) this study advances the literature on Saudi women in organizations by focusing on resistance as a point of entry and analysis; (2) we add a less antagonistic relationship between power/resistance, and reconceptualize agency/resistance as one inclusive of subtle and individual forms of resistance, and one that moves beyond the limits of the liberal imaginary; (3) our study also adds to the burgeoning scholarship on workplace resistance in non-Western contexts, which advocates for situated knowledge and the decolonization of management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".