International Perspectives of Diversity, Equity, and Inclusion
Bibliographic record
Abstract
International Perspectives of Diversity, Equity, and Inclusion, the seventh in the Research on Social Issues in Management series, includes a collection of contributions from around the globe. The amalgamation of these perspectives together broadens the scope of diversity, equity, and inclusion (DEI) research and practice and offers insights that extend beyond the U.S.-focused research that dominates the field. The book addresses unique facets of organizational diversity and brings to bear diverse cultural contexts, historical legacies, and socio-political considerations from regions as varied as South Korea, England, Ireland, Puerto Rico, Norway, Australia, Germany, Malaysia, Japan, Canada, France, India, Belgium, and Sweden. The contributions challenge prevailing assumptions and expand the theoretical and practical boundaries of the field by providing actionable strategies through which to approach DEI in more culturally sensitive and globally relevant ways
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".