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Pressures on Sports Volunteers Arising from Partnerships with the Central Government

2003· article· en· W2059360118 on OpenAlexvenueno aff
Geoff Nichols, Peter Taylor, Lindsay Findlay-King, Kirsten Holmes, R. Sam Garrett

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)ClubContext (archaeology)Central governmentSport managementPolitical scienceScale (ratio)Public relationsWork (physics)Affect (linguistics)Public administrationPsychologyLocal governmentMedicineEngineeringGeography

Abstract

fetched live from OpenAlex

This paper uses results of two research projects investigating the pressures on volunteers in UK sport to illustrate the implications of partnerships between national governing bodies of sport and the central government. National governing bodies of sport receive funding from the central government via Sport England and UK Sport. This funding has conditions attached. The conditions will affect volunteers at the national level of the NGB, but will also cascade down to volunteers in the sports clubs. Thus, they add to the complexity and scale of tasks performed by club level volunteers, who require additional support to perform them. For most NGBs, this external funding is a very significant proportion of their income, so it may have a corresponding impact on the development of the sports and the work of volunteers. The conditions attached to support can be understood in the broader context of a professionalisation of sport in the voluntary sector. As such, the pressures from the central government are inevitable, but volunteers can also be supported by their NGBs and Sport England.

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)0.001
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 score0.825
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.295
Teacher spread0.263 · 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

Citations21
Published2003
Admission routes1
Has abstractyes

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