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Record W204701233 · doi:10.1123/ssj.19.2.206

The “Anti-Jock” Movement: Reconsidering Youth Resistance, Masculinity, and Sport Culture in the Age of the Internet

2002· article· en· W204701233 on OpenAlexaff
Brian Wilson

Bibliographic record

VenueSociology of Sport Journal · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOpposition (politics)MasculinityThe InternetSociologyResistance (ecology)Youth cultureGender studiesConsumption (sociology)PsychologyAdvertisingSocial psychologyPolitical scienceSocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

This paper explores issues relevant to youth, masculinity, Internet, and sport studies through a case study of the “anti-jock” (cyber)movement. The anti-jock movement is group of self-described “marginalized youth” who, through the production and consumption of anti-jock Websites, express dissatisfaction with and anger toward institutions that uncritically adulate hyper-masculine/high-contact sport culture and the athletes who are part of this culture (i.e., the “jocks"). Through these Websites, strategies of resistance against the “pro-jock” establishment are offered. An analysis of these sites acts as a departure point for considering how existing approaches to understanding youth cultural activity might be integrated with strands of new social movement theory to better account for more advanced forms of youth opposition/activism that have emerged following (and as a partial result of) the mass adoption of Internet-based communication. Also included is a discussion of the potential for anti-jock Websites specifically, and youth produced alternative-media generally, to empower youth and/or alter the oppressive forces that impact various “outsider” youth groups. The paper concludes with suggestions for future work that would extend and evaluate the ideas proposed here.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.280
Teacher spread0.227 · 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 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

Citations43
Published2002
Admission routes1
Has abstractyes

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