MétaCan
Menu
Back to cohort
Record W2983405183 · doi:10.5772/intechopen.89192

Sport for Development and Peace: Current Perspectives of Research

2019· book-chapter· en· W2983405183 on OpenAlexaff
Tegwen Gadais

Bibliographic record

VenueIntechOpen eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversité du Québec à Montréal
FundersEmerald Publishing
KeywordsDiplomacyPolitical scienceField (mathematics)Sustainable developmentContext (archaeology)Cohesion (chemistry)Public relationsPoliticsGeography

Abstract

fetched live from OpenAlex

Sport for Development and Peace (SDP) is an international movement that began in the 2000s with the Millennium Development Goals (2000–2015) and is currently continuing around the United Nations’ Sustainable Development Goals 2015–2030, driven by international organizations such as UNESCO. Often located in an international development context, organizations and associations use sport as a vehicle to reach several social and humanitarian missions (e.g., education, social cohesion, health, reintegration, diplomacy, and peace). This chapter presents the origins and objectives of the SDP, but it also looks at current research in the field. Since 2010, studies have significantly increased in the field around four main areas (macrosociological, field explorations, program management and evaluation, and literature reviews). This chapter also provides illustrations of SDP research projects, axis of tensions between practice and theory, and perspectives for future research in the field.

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)0.004
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.010
Science and technology studies0.0020.009
Scholarly communication0.0140.013
Open science0.0020.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0150.004

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 head0.175
GPT teacher head0.445
Teacher spread0.271 · 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
GenreReview

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

Citations19
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueIntechOpen eBooksSame topicSport and Mega-Event ImpactsFrench-language works237,207