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Record W4417320167 · doi:10.1080/17430437.2025.2596514

Eating’s cheating and the peculiarity of male professional road cycling

2025· article· en· W4417320167 on OpenAlexaff
James J. Brittain

Bibliographic record

VenueSport in Society · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsAcadia University
Fundersnot available
KeywordsCheatingCyclingAgency (philosophy)Context (archaeology)Punitive damages

Abstract

fetched live from OpenAlex

Itself a unique outlier when related to for-profit sport, contemporary professional male road cycling also provides a subject that can be framed as an outsider. Where most high-performance sports applaud expressions of visible musculinity, the peloton demarcates power not through strength-as-observable but rather the absence thereof. Through an inversion of meaning, the most dominant are the most diminished. Here, those who embody the greatest qualitative and quantitative representations of success exhibit a physique more akin to a pre-pubescent boy than chiseled Adonis. Through a critique of capital and the sport’s normalizing of disordered eating, the work centres the pro male road cyclist as an under-regarded but noteworthy sociality. Of broad value to the fields of applied, physical, and social science, the work tracks how those, if to succeed, are compelled to take up a different depiction of the elite athlete. When weighed against others, this cohort’s professional relation to power, food, and gender interrupts certain expectations, constructions, and constitutions that signal the need for such a sociological analysis of cycling’s current practices and their impacts.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.264
Teacher spread0.258 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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