The governing of governance: metagovernance and the creation of new organizational forms within Canadian sport
Bibliographic record
Abstract
This article examines how the creation of new governing arrangements (i.e., new organizational forms and new actors) has enabled government (Sport Canada) to strengthen its control and influence over Canadian sport illustrated through two empirical case studies of newly created organizational forms. More specifically, we draw upon the metagovernance approach to examine the inter-organizational dynamics between Sport Canada and quasi-autonomous organizational entities (Own the Podium and Sport for Life) and the nature of these new governance arrangements. The analysis highlights the similar trajectories of the two case-study organizations and reveals similar underlying patterns of control by Sport Canada in that both newly created entities have been used to strengthen the governmental agencies’ capacity and reach over the sport sector. Furthermore, the study reveals how these resource-dependent organizations are being utilized and leveraged by government, often through negotiation, diplomacy, and other informal mechanisms, to achieve its own objectives. More broadly, our analysis highlights the underlying mechanisms through which these newly formed networked arrangements operate.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.030 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".