Towards a critical geography of physical activity: Emotions and the gendered boundary‐making of an everyday exercise environment
Bibliographic record
Abstract
In this paper, we put forward a proposal for a critical geography of physical activity that attunes to experience while centring on the socio‐spatial processes and power structures enabling and constraining physical activity participation. Drawing on our research that explored women's and men's emotional geographies of an everyday exercise environment – the gym – in a Canadian city, we show how this approach can identify otherwise invisible environmental influences on physical activity participation. Our thematic analysis reveals that the gym environment is generative of three place‐based emotive processes of dislocation, evaluation, and sexualisation that collectively configure an unevenly gendered emotional architecture of place. Through this interstitial structure, the boundaries of localised hierarchies of masculinities and femininities become felt in ways that create tensions and anxieties, which in turn reinforce gendered boundaries on physical activity participation. Two additional themes reveal how gendered motivation and individual factors mediate negative emotional experiences. Our findings indicate that emotional geographies are one way in which gender disparities in physical activity are naturalised at the scale of the everyday exercise environment. Interventions for gender equity in physical activity would benefit from being empathetically attuned to the subtleties of place‐based experiences. More widely, bringing emotions into geographies of physical activity sheds light on the larger question of the role of place in (re)producing gendered health inequities, with implications for geographical research on health and social justice. Future critical geographical inquiry is necessary to ensure that public health interventions are grounded in the experiential realities of practising physical activity in particular places.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.081 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".