Sport and Livelihoods: From Outcomes to Experiences
Bibliographic record
Abstract
This research aims to add to the limited but growing body of literature on the potential impacts of Sport for Development and livelihood programming. Previous research has predominantly focused on prescribed outcomes and reinforcing neoliberal capitalist ideologies. More specifically, the purpose of this qualitative study is to explore the use of sport for livelihood programming in supporting the needs of youth facing barriers at one Sport for Development facility. This research is guided by two key objectives: (a) How do participants (current and past) describe and interpret their experiences within a Sport and Livelihood program? (b) How are contemporary constructions of class, race, gender, poverty, (dis)ability and culture shaped through this programming? Semi-structured interviews were conducted with 7 participants of the MLSE LaunchPad Fellowship Program. Participants’ ages ranged from 19 to 25; 4 were males and 3 females; 6 identified as BIPOC, while 1 individual identified as white. Thematic analysis was an accessible and flexible way to identify patterns within and across data in relation to participants’ lived experience, perspectives, behaviours, and practices.\nThe four aggregate themes were discussed by participants: Program Experience, Organizational Supports, Workplace Structures and Livelihoods. A further subset of twelve themes was also identified providing a deeper level of nuance for the aggregate themes. Findings suggested that programming within the field of SfD and Livelihoods may (re)produce inequality by providing precarious working conditions for participants. Future research is a needed to explore programming from an interdisciplinary, if not transdisciplinary, perspective. There is a need to understand the variety of forces—economic, political, cultural, psychological—that (re)shape SfD and livelihoods.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.011 |
| 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".