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Record W3137845226 · doi:10.1080/17430437.2021.1900828

Exploring Vietnamese sport for development through the capabilities approach: a descriptive analysis

2021· article· en· W3137845226 on OpenAlexaff
Michael Dao, Simon C. Darnell

Bibliographic record

VenueSport in Society · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVietnameseSociologyDevelopment theoryBridging (networking)Engineering ethicsManagement sciencePublic relationsKnowledge managementPolitical scienceEngineeringComputer scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

This paper explores and illustrates empirically how the Capabilities Approach (CA) can be used to frame and understand Sport for Development (SfD) practices. Based on research with a SfD project in Vietnam, we show how the CA is compatible with understanding SfD practices, and even its intended outcomes, particularly gender equity and sports participation for all. Hence, we offer one of the first empirical understandings of the CA to SfD, thus furthering the bridging of theory and practice in the study of SfD. We argue that the CA as a development theory provides an appropriate theoretical basis for SfD because it aligns with the ways in which SfD practitioners approach their work. We conclude that SfD practices at their core seek to contribute to providing a life worthwhile by promoting opportunities for individuals to experience various Central Capabilities.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.220
GPT teacher head0.339
Teacher spread0.119 · 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 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

Citations13
Published2021
Admission routes1
Has abstractyes

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