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Record W2977064590 · doi:10.1123/jsm.2019-0126

Development, Gender and Sport: Theorizing a Feminist Practice of the Capabilities Approach in Sport for Development

2019· article· en· W2977064590 on OpenAlexaff
Sarah Zipp, Tavis Smith, Simon C. Darnell

Bibliographic record

VenueJournal of Sport Management · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSociologyDevelopment theoryContext (archaeology)UnpackingIdeologyFeminismEpistemologyFeminist theoryEngineering ethicsGender studiesPoliticsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Sport for development (SFD) research and practice has become more critically examined recently, with many scholars calling for better understanding of how and why sport might contribute to the global development movement. Developing and refining theoretical approaches is key to unpacking the complexities of SFD. Yet, theory development in SFD is still relatively young and often relies on oversimplified theory of change models. In this article, the authors propose a new theoretical approach, drawing upon the capabilities approach and critical feminist perspectives. The authors contend that the capabilities approach is effective in challenging neoliberal ideologies and examining a range of factors that influence people’s lived experiences. They have woven a “gender lens” across the capabilities approach framework, as feminist perspectives are often overlooked, subjugated, or misunderstood. The authors also provide an adaptable diagrammatic model to support researchers and practitioners in applying this framework in the SFD context.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.304
Teacher spread0.269 · 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.

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

Citations28
Published2019
Admission routes1
Has abstractyes

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