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Record W4289815972 · doi:10.1123/smej.2021-0023

Examining the Use of Postcolonial Management Theory in Sport Management Education: Strategies to Enhance Student Learning of Colonial Histories and Challenge Dominant Ideologies

2022· article· en· W4289815972 on OpenAlexaff
Mitchell McSweeney, Georgia Teare, Helen Liu

Bibliographic record

VenueSport Management Education Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of OttawaYork University
Fundersnot available
KeywordsPerformative utteranceIdeologyPerformativitySociologySport managementDominance (genetics)ColonialismPedagogyPublic relationsEngineering ethicsEpistemologyPoliticsPolitical scienceGender studiesEngineeringLaw

Abstract

fetched live from OpenAlex

There remains limited work that examines the use of postcolonial theory in sport management, and even less so in sport management education. The purpose of this paper is to outline a performative approach, guided by postcolonial management theory, and its utilization within sport management classrooms. The paper highlights two forms of performativity—critical and progressive—and identifies and discusses specific pedagogies that educators may adopt for student learning about the dominance of Westernized understandings of management and organizations. Integrating a postcolonial management theory, performative approach in sport management education in conjunction with socially just pedagogies seeks to acknowledge and disrupt a reliance on Westernized ideologies. The paper concludes by discussing the significance of postcolonial management theory for sport management education.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0080.004
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.334
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

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