Indigenous Peoples and Organization Studies
Bibliographic record
Abstract
This essay encourages scholars of management and organization studies (MOS) to critically reflect on how Indigenous peoples and their knowledges have been, and continue to be, systemically discriminated against. This discrimination is the result of colonization; it has deeply impacted and continues to affect which knowledges and practices are valued and embraced. The impact of colonization is mirrored in MOS via processes and actions within the academic setting and our business schools. The result is the continued marginalization of Indigenous peoples and their knowledges. We propose a shift in how MOS scholars approach research in relation to non-western societies to counter, and hopefully end, these continued practices of discrimination in our business schools. Specifically, we argue that demarginalizing Indigenous research in academia and going beyond 'cosmetic indigenization' in our business schools are new, collaborative ways of rethinking indigeneity and breaking down the current barriers in MOS that reinforce and perpetuate the systemic discrimination against Indigenous peoples, their knowledges and practices.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.028 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".