Bibliographic record
Abstract
This chapter explores two soccer pilot micro-projects implemented in Australia, a Global North state with a strong sporting identity, but one that continues to contend with ongoing structural inequalities. The projects focussed on two marginalised groups in Western Sydney: African refugees and First Nations peoples. Framed within discussions of Australia’s history, politics, and socio-cultural dynamics, the chapter examines these initiatives as case studies in sport-for-development. It contextualises Australia’s unique position at the intersection of Global North/South dynamics and examines the nation’s historical treatment of Indigenous populations and evolving immigration policies. The projects tested the use of soccer as a tool for fostering community cohesion and integration. The refugee programme highlighted the cultural relevance of soccer and its potential to address social isolation, whilst the initiative with First Nations youth emphasised skill-building and engagement. The work is informed by data from semi-structured interviews. Both projects yield insights into the value and limitations of pilot projects and the sport as a medium for social inclusion. They also underscore the challenges of sustaining impact and navigating cultural power dynamics in such ventures. The final sections articulate understandings of Australian popular culture, drawing out some key lessons from these projects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".