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Record W2281998958 · doi:10.1177/0002764216632843

A Commentary on Sport and Terrorism From the Vantage of Sport Psychology

2016· article· en· W2281998958 on OpenAlexaff
Robert J. Schinke, Kerry R. McGannon, Rebecca Busanich, Yang Ge

Bibliographic record

VenueAmerican Behavioral Scientist · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsLaurentian University
Fundersnot available
KeywordsTerrorismSport psychologyMainstreamPsychologyRelation (database)Thematic analysisCriminologySocial psychologySociologySocial sciencePolitical scienceLawQualitative research

Abstract

fetched live from OpenAlex

The authors of this article engage in a commentary regarding broad thematic areas identified within the special issue on sport and terrorism. The commentary begins with the authors situating themselves within the field of sport psychology, and as critical scholars more specifically within the emerging cultural sport psychology genre. To further contextualize certain aspects of criticality outlined from a sport psychology vantage, a brief story is offered where one of the authors shares his experience as a volunteer during the 1996 Olympics as a volunteer, where he was first exposed to sport and terrorism. Next, discussions are taken up in relation to four themes that we identified as relevant from the foregoing sport psychology vantage: (a) sport events and terrorism as mainstream, (b) terrorism and the media as conduit, (c) sport as a recruitment tool toward and away from terrorism, and (d) sport as an antidote to terrorism. The commentary authors conclude with a summation followed by parting critical reflections in relation to the current and future status of this emerging area.

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)0.009
metaresearch head score (Gemma)0.051
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.028
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0130.013
Scholarly communication0.0070.005
Open science0.0030.004
Research integrity0.0280.029
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.375
Teacher spread0.349 · 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
GenreCommentary

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

Citations2
Published2016
Admission routes1
Has abstractyes

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