Moving toward trust and partnership: an example of sport-related community-based participatory action research with Aboriginal people and mainstream academics
Bibliographic record
Abstract
Purpose – The purpose of this paper is to critically examine the authors own assumptions made as academics using two examples from a research project with an Aboriginal community. The first attempt features a project that silenced the community. Later work engaged the community through tenets of community-based participatory research (CBPR) and a sport development project (SDP). Design/methodology/approach – This project explores a shift from a mainstream qualitative approach steeped in post-positivism to a de-colonizing methodology which opened up a space for a SDP. Findings – Mainstream research methodologies tend to silence marginalized communities and overlook local cultural practices. Effective community programming requires extensive consultation, and an approach that centralizes local voices. Research limitations/implications – Current understandings are limited to one Aboriginal Reserve. Practical implications – Recommendations are proposed concerning how researchers might embark on practices that support the reversal of colonization and improve relations among people from two cultures previously in conflict. SDP initiatives and applied sport research grounded in CBPR are proposed as conduits to bettering relations among cultures in conflict. Originality/value – The reader is provided with an example of how to attain goals of SDP at the local level through cultural praxis and a CBPR methodology.
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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 | 0.070 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.045 | 0.055 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.005 | 0.025 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".