MétaCan
Menu
Back to cohort
Record W287750112 · doi:10.1079/9781780642529.0018

Events and social capital.

2013· book-chapter· en· W287750112 on OpenAlex
Laura Misener

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCABI eBooks · 2013
Typebook-chapter
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsSocial capitalPublic relationsCommunity engagementAffect (linguistics)Political scienceSociologySocial science

Abstract

fetched live from OpenAlex

This chapter focuses on the potential of sporting events to help build stronger communities and influence the development of community-level social capital. The purpose is to focus on the emergence of ways to utilize sporting events to affect communities in a positive manner and showcase how events can be leveraged for greater social benefits. By situating the discussion in relevant theoretical frameworks, this chapter identifies and examines the positive potential of the events processes as a way of building social capital, engaging communities and improving the overall social well-being of community members. A case study of the 'Playing for Keeps' strategy of the 2012 Ontario Summer Games and the 2015 Pan American Games in Toronto, Canada, is used to locate the analysis of key concepts related to leveraging positive social impact, social leveraging, community social capital and community engagement.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.259
Teacher spread0.229 · 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