MétaCan
Menu
Back to cohort
Record W4404400665 · doi:10.1177/21674795241299025

Defamiliarizing Concussions: Sports Fandom, Injury, and Potential Attitudinal Shifts

2024· article· en· W4404400665 on OpenAlexaff
Nathan Kalman-Lamb, Derek Silva

Bibliographic record

VenueCommunication & Sport · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsThe King's UniversityWestern UniversityUniversity of New Brunswick
Fundersnot available
KeywordsFandomSports injuryPsychologyApplied psychologyAdvertisingSociologyPhysical therapyMedicineMedia studiesBusiness

Abstract

fetched live from OpenAlex

In this article, we examine whether modes of representation that disrupt and defamiliarize the naturalized understandings fans share about the legitimacy and necessity of spectacular violence and sacrifice in sport can have the potential to reframe fan attitudes and investments. We explore the social cognitive and attitudinal shift towards traumatic brain injury (TBI) and injury more broadly in American football of first year students with a stated investment in the spectacle of high-performance sports after viewing Josh Begley’s 2018 short film Concussion Protocol. By comparing the responses of students at the beginning of the semester to their responses immediately after viewing the film, this project reveals how placing fans of sport in a face-to-face relationship with athletic laborers can challenge preexisting assumptions about normalized violence in sport, ultimately effectuating a potentially new and more humane attitude to athletic spectatorship.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.005
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.334
Teacher spread0.303 · 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.

Study designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCommunication & SportSame topicSports, Gender, and SocietyFrench-language works237,207