A critical geography of physical activity: Investigating the role of gender in gym environments
Bibliographic record
Abstract
This thesis develops a critical geography of physical activity by examining the implications of socio-spatial processes at the scale of the everyday exercise environment for gendered inequities. Around the world, men are more active than women. Meeting recommended physical activity guidelines significantly reduces risk of a range of chronic conditions and premature death; yet, on the whole, women are missing out on these health benefits as compared to their male counterparts. Gyms—although routine places for exercise—are conspicuously absent from health geography research. In this thesis, I investigate the central question: What is the role of an everyday exercise environment, specifically the gym, in the gendering of physical activity? Situated in a conceptual framework linking literature on gender, health geographies, and emotional geographies, my research design comprises an in-depth, multi-method qualitative study incorporating semi-structured interviews, participant-generated drawing, and journaling with 52 women and men in a mid-sized Canadian city. First, I investigate how gender manifests in gym environments and identify five multisensorial gendered performativities of place: bodily materialities; the soundscape; visual fields; the physical environment; and the imaginary. Next, I examine how gender influences gym-users’ practices and mobilities and identify three socio-spatial processes at play (embodying gender ideals, policing gender performance, and spatializing gender relations), along with a fourth theme illustrating the agency some individuals interject to disrupt gender hegemony. I then turn to consider how gender matters in the emotional geographies of the gym where I find three processes (dislocation, evaluation, and sexualization) that create a sense of gender displacement and configure an unevenly gendered emotional architecture of place, while individual factors can mediate negative emotional outcomes. My findings demonstrate that while gyms are potentially sites for health promotion, they are also places where gendered inequities in health opportunities emerge. I argue that addressing gender inequities requires attention to the complexities of the socio-spatial processes that naturalize, as well as challenge, gender differences and disparities in the very places where physical activities are undertaken. Interventions to improve gender equity in physical activity participation need to account for the gendered features of everyday exercise environments.
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 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.048 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".