“ <i>We just want to get fit too</i> ”: belonging and inclusion in the gym
Bibliographic record
Abstract
Psycho-emotional disablism refers to the negative effects on the psychological well-being of people with a disability that arise from inaccessible physical environments and stigmatising interactions. In gyms, psycho-emotional disablism poses a major barrier to social inclusion. To foster inclusive gym environments, wherein people of all abilities can feel welcome, it is critical to understand the experiences of people with and without a disability. This study aimed to understand the social environment in gyms by interviewing diverse participants. Thirty-five adults with (~37%) and without a disability (~63%) participated. Reflexive thematic analysis of the interview transcripts resulted in three themes related to sense of belonging, the integration of people with diverse abilities, and the relationship between physical design and social inclusion. Participants described feelings of intimidation associated with gym experience and body ideals in the gym, illustrating a need for strategies to enhance comfort and sense of belonging through a more inclusive culture. Gym cultures that facilitated belonging and inclusion encouraged integration among diverse users, potentially leading to greater recognition, acceptance, and support for people with a disability. In addition to inclusive social environments, accessible physical design influenced the acceptance and integration of diverse users in gyms by welcoming users of all abilities into the space. Ultimately, gyms that promote inclusion throughout the facility, encompassing design and social interactions, enable all users to feel welcome, included, and like they belong, promoting equitable opportunities for people with and without a disability to engage in gym-based exercise.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".