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Record W4387937583 · doi:10.3389/fspor.2023.1256885

Social entrepreneurship in sport: a peripheral country perspective

2023· review· en· W4387937583 on OpenAlexaff
Denise Kamyuka, Laura Misener, Marisa Tippett

Bibliographic record

VenueFrontiers in Sports and Active Living · 2023
Typereview
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsWestern University
FundersDeutsche Sporthochschule Köln
KeywordsPerspective (graphical)EntrepreneurshipSocial entrepreneurshipEconomic geographySociologyPolitical scienceEconomicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

For the past decade, scholars have been working towards developing a robust theory of social entrepreneurship in sport (SES). However, SES theory remains void of peripheral country perspectives and thus perpetuates the Eurocentric views of entrepreneurship. This paper used a decolonial feminist lens and Whittemore and Knafl’s methodology to conduct an integrated review of SES literature written in or about a peripheral country context. The review examined how scholarship from and about this context had considered geographical and culturally specific perspectives in the development of SES theory. A total of n = 1971 papers were retrieved, with only n = 12 providing relevant peripheral country context. This scarcity of literature indicates that the current theory of SES lacks peripheral country perspectives. Many papers in this review (n = 5) are written by authors in or from a peripheral country. Their contributions to SES literature revealed the decolonial feminist approaches that centralize alternative perspectives and added plurality to the definition of SES. The findings revealed the nuanced theoretical approaches to SES and highlighted the gaps in this context. The review shows how, despite the rise in social enterprises that focus on gender equity and the economic inclusion of women, gendered studies were still very scarce.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.081
GPT teacher head0.341
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

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