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Record W2734851745 · doi:10.1123/ssj.2016-0159

Re-Assembling Sport for Development and Peace Through Actor Network Theory: Insights from Kingston, Jamaica

2017· article· en· W2734851745 on OpenAlexaff
Simon C. Darnell, Richard Giulianotti, P. David Howe, Holly Collison

Bibliographic record

VenueSociology of Sport Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Toronto
FundersEconomic and Social Research Council
KeywordsSophisticationIdeologyActor–network theoryAgency (philosophy)Field (mathematics)SociologyEpistemologyPolitical scienceSocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Some recent appraisals of Sport for Development and Peace (SDP) research have found it to be deterministic and ideological, and lacking sophistication and specificity with regards to theory and method. Notably, such criticisms dovetail with the foundations of Actor Network Theory (ANT). Based on fieldwork in Kingston, Jamaica, we draw on ANT to ‘re-assemble’ the understanding of SDP programs by examining their constitutive elements. The results illustrate the connections necessary for SDP to cohere, and the range of actors in the field, including international funders, funds themselves, and concepts regarding sport’s development utility. Investigating these assemblages facilitates a non-deterministic understanding of the ways in which sport is mobilized in the service of development and peace, while allowing for a nuanced and empirically sound assessment of power and agency.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.073
GPT teacher head0.360
Teacher spread0.287 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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