Behind the scenes of sport for development: Perspectives of executives of multinational sport organizations
Bibliographic record
Abstract
This article reports findings from a study designed to examine cricket’s role as an international development tool – with a particular focus on how decisions are made at the highest institutional levels to support cricket-related development initiatives. Data for the study are drawn from interviews with executives in the International Cricket Council and the Marylebone Cricket Club who were asked about how and why decision-makers in their organizations chose to engage in development-related work. The study is informed by literature on postcolonialism, sport for development and peace, global politics and the sociology of cricket. The results illustrate that: (a) a select group of executives in the International Cricket Council and the Marylebone Cricket Club make decisions hierarchically, and that decisions reflect organizational mandates; (b) decision-makers tend to be dismissive of critiques of sport for development and peace, with notable exceptions; and (c) the goals and implications of development-related programmes are portrayed differently to different audiences. This article concludes with commentary on the ways that cricket continues to be implicated in postcolonial relationships and on the processes of decision-making in organizations governed by neoliberal policies.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".