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Record W3048508692 · doi:10.1080/14649365.2020.1806344

<i>‘I wouldn’t take the risk of the attention, you know? Just a lone girl biking’</i>: examining the gendered and classed embodied experiences of cycling

2020· article· en· W3048508692 on OpenAlexafffundabout
Léa Ravensbergen

Bibliographic record

VenueSocial & Cultural Geography · 2020
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGirlEmbodied cognitionCyclingSociologyGender studiesPsychologyEpistemologyHistoryDevelopmental psychologyPhilosophy

Abstract

fetched live from OpenAlex

This paper frames the embodied experience of bicycling using theories of performativity and materiality. In doing so, the paper provides insights into embodied processes that regulate the gendered and classed cycling body across age. Drawing from interviews completed with newcomers to Toronto enrolled in a bicycle mentorship program, this paper highlights how context-specific social norms exist around who is read as cycling appropriately. Two norms consistently discussed are that cycling can be at odds with femininity and that it is a symbol of poverty. These norms act as discursive regulatory frameworks for gender and class performativity. Cycling can also be an experience of ‘intense embodiment’ in that it can bring the absent body back into consciousness. This experience is dynamic and elicits diverse emotions. Furthermore, cycling is not only found to increase people’s awareness of their materiality, but also their bodily fluids challenge the notion of ‘secure’ bodily boundaries. These material processes can be gendered and/or classed, and can affect access to mobility and public space. By studying identity formation processes as they relate to cycling, this paper sheds light on the power-laden underpinnings of identity-based differences in cycling.

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)0.001
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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.007
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.055
GPT teacher head0.307
Teacher spread0.252 · 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

Citations43
Published2020
Admission routes3
Has abstractyes

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