Indigenous and gendered persons and peoples in business ethics education: Intersections of Indigenous wisdoms and de Beauvoirian existentialism
Bibliographic record
Abstract
Abstract The purpose of this paper is to explore how business ethics textbooks include Indigenous and gendered persons and peoples and whether they acknowledge Indigenous philosophies and theories. We explore 363 cases from eighteen (18) business ethics textbooks. A form and theme based content analysis was employed to help us better understand the inclusion, obfuscation and omission of Indigenous and gendered persons. A purpose of business ethics education is to disrupt injustice and oppressive practices in business. We find that business ethics education can provide more inclusive and respectful cases as it relates to Indigenous and gendered characters. There are cases that marginalize, obfuscate and omit Indigenous peoples, females, and gender diverse persons. This study contributes to diversity scholarship by identifying ways in which Indigenous and gendered persons and peoples can be included in management and business ethics education.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".