Social inclusion through sport for women experiencing homelessness
Bibliographic record
Abstract
© 2020, Griffith University. All rights reserved. Background: People experiencing homelessness have been described as one of the most socially excluded groups, particularly homeless women. Exploring the barriers and facilitators of social inclusion for women experiencing homelessness, in particular their experience with sports-based activities, may identify key criteria to improve and facilitate their access to community activities and result in opportunities for increased inclusion. Methods: Qualitative thematic analysis was used to explore women’s homelessness, social inclusion, and their interest and engagement in sportbased activities. In a mid-sized city in Canada, data was collected using semistructured interviews with eleven women residing in a shelter. The data were analyzed for themes relating to the research questions. Four corresponding themes were derived from the interviews: (a) poverty is the main source of social exclusion, (b) housing is not necessarily a prerequisite for social inclusion, (c) women play sports too; it’s not just for men, and (d) Purposeful rather than passive recruitment boosts inclusion. These themes represent the barriers and facilitators of social inclusion that the participants experienced, as well as their experiences and interests in sports. Conclusion: The findings revealed that while women who are experiencing homelessness may be interested in participating in sport activities as an opportunity to improve aspects of their social inclusion, they face many barriers in accessing sport activities. The findings of this study may inform organizational and government policy, and future research. Further intersectional research is needed to understand how gendered experiences of homelessness intersect for Indigenous or racialized persons.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".