Research Partnerships in Sport for Development and Peace: Challenges, Barriers, and Strategies
Bibliographic record
Abstract
Research partnerships between scholars and sport for development and peace (SDP) organizations are common, but firsthand accounts of the challenges and barriers faced by scholars when forming and sustaining partnerships are rare. Therefore, the purpose of this study was to examine them, and to uncover strategies to overcome these challenges across different partnership contexts. Eight prominent SDP scholars were interviewed. Guided by collaboration theory and the partnership literature, findings revealed challenges included navigating the political and organizational landscape; securing commitments from organizations with limited resources; negotiating divergent goals, objectives, and understandings; and conducting long-term evaluations and research. Strategies to address these issues involved developing strategic partnerships, cultivating mutual understanding, building trust, starting small, finding the cause champion, and developing a track record of success. Key theoretical and practical implications are drawn forth, as well as intriguing future research directions.
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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 | 0.061 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".