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Record W1995706148 · doi:10.1080/17430431003780088

The historical mediatization of BMX-freestyle cycling

2010· article· en· W1995706148 on OpenAlexaff
Wade Nelson

Bibliographic record

VenueSport in Society · 2010
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsCentralityDominance (genetics)NegotiationMediationMedia studiesPolitical scienceSociologyExploitAdvertisingPublic relationsSocial scienceBusinessComputer scienceComputer security

Abstract

fetched live from OpenAlex

This paper traces the mediatization of BMX-freestyle cycling over the past four decades through an examination of the centrality of particular media of communication and particular texts within this sport. It is argued that the history of BMX is inseparable from the history of the activity's mediation. Indeed, the historic rise and fall of the sport with regard to industrial success can be correlated with the appearance and disappearance of disseminating institutions such as particular special-interest magazines. Furthermore, these magazines have been the site of introductions to, and negotiations with, other competing media throughout the history of the activity. In the early twenty-first century, digital media have increasingly challenged the dominance of older media that have served/exploited this sport. It is probable that this particular activity, and the media that serve and exploit it, will continue to have a complex, co-dependent relationship.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.006
Scholarly communication0.0040.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.012
GPT teacher head0.289
Teacher spread0.276 · 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 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

Citations15
Published2010
Admission routes1
Has abstractyes

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