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Record W2920659710 · doi:10.1057/978-1-137-43944-4_9

Athletes, NGOs, and SDP

2019· book-chapter· en· W2920659710 on OpenAlexaffabout
Simon C. Darnell, Russell Field, Bruce Kidd

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of ManitobaUniversity of Toronto
Fundersnot available
KeywordsMainstreamNorwegianCivil societyPolitical scienceTransparency (behavior)AthletesCorporate governancePublic relationsPublic administrationEconomic growthManagementLawPoliticsMedicineEconomics

Abstract

fetched live from OpenAlex

The national sport cultures of countries like Norway and Canada, which in part motivated international sport aid in the late twentieth century, also led to a generation of high-performance athletes concerned with social issues and schooled in the efficacy of sport-for-good. This increasingly activist generation argued for greater transparency in sport governance but also believed in the power of sport to address social ills. Prominent among them was Norwegian speed skater Johann Olav Koss, who founded the sport-for-development-focused non-governmental organization (NGO) Right to Play. The international profile achieved by NGOs like Right to Play and the Mathare Youth Sports Association, based in Kenya, illustrates the prominence that sport-for-development achieved in the first decade of the twenty-first century. Their rise to prominence also points to the influence that civil society organizations would come to have within the Sport for Development and Peace sector, as well as the challenges that sport NGOs would have in integrating into the mainstream development sector.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.004
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0260.004

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 head0.029
GPT teacher head0.269
Teacher spread0.240 · 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
GenreOther

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

Citations0
Published2019
Admission routes2
Has abstractyes

Explore more

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