‘One mirror in another’: Managing diversity and the discourse of fashion
Bibliographic record
Abstract
In this article, we report on a multi-sited ethnographic study that investigates how the discourse of fashion influenced the design and implementation of workplace diversity management programs in six organizations. These organizations, from the Canadian petroleum and insurance industries, were manipulated by an institutional field of consultants and experts into adopting relatively superficial initiatives that lacked local relevance, and produced a high level of organizational cynicism regarding diversity. In our analysis, we particularly explore one adverse effect of this discourse of fashion; that it may trigger a form of meaningless imitation by organizations adopting diversity management initiatives, resulting in superficiality and organizational cynicism. At the same time, the discourse of fashion may also hold the key to enable meaningful change, for it has a powerful influence on organizational practitioners. Our article suggests that organizations need to be aware of the institutional field, and engage with it in a manner that imbues their initiatives with local relevance, for their initiatives to contribute to meaningful organizational change.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.019 | 0.051 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| 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".