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Record W4414121026 · doi:10.1177/01937235251370664

What Can the Running Body Do? The Running Machine's Affective Possibilities and the Limits of Language

2025· article· en· W4414121026 on OpenAlexafffund
Jean Ketterling, Bridgette Desjardins

Bibliographic record

VenueJournal of Sport and Social Issues · 2025
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSubjectivityEmbodied cognitionMainstreamAssemblage (archaeology)Action (physics)Everyday life

Abstract

fetched live from OpenAlex

While others have suggested that action sports offer avenues of escape from neoliberal imperatives like maximizing health and self-regulation, we argue that even the most mainstream of sports-amateur road running-holds similar potential. Using data from 20 "running reflections," we explore running's everyday affective intensities using Deleuzo-Guattarian theory. We conceptualize running as a machinic assemblage that shapes what the body can do in myriad ways. We argue that while the running machine produces neoliberal imperatives and the disciplined subjectivity of "runner," those almost inarticulable affects that runners struggle to express reveal deterritorial possibilities that challenge the stratification of running as a practice shaped by health and fitness discourse. Additionally, we show that it is important to cultivate methodologies and analytic strategies that excavate beneath the surface of participants' stratified language, because runners' tendency to default to wellness language-order-words-for the sake of effective communication in a world where neoliberal logics are most easily articulated and understood may elide other affective and embodied analytic possibilities in the form of a-grammatical deterritorializations.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.334
Teacher spread0.321 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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