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Record W4309190858 · doi:10.1177/01708406221141545

Indigenous Peoples and Organization Studies

2022· article· en· W4309190858 on OpenAlexafffund
François Bastien, Diego M. Coraiola, William Foster

Bibliographic record

VenueOrganization Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of VictoriaUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenizationIndigenousCritical management studiesSociologyTraditional knowledgeEnvironmental ethicsPolitical scienceSocial scienceAnthropologyEcology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.236
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations86
Published2022
Admission routes2
Has abstractyes

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