A Comparative Analysis of Nonprofit Policy Network Governance in Canada
Bibliographic record
Abstract
Across Canada, provincial governments and nonprofit network leaders are engaged in a “third wave” of consultations, policy dialogues, and policy alignment strategies. Unexplored to date is how nonprofit policy networks are governed and structured. Network structures could have important implications for policy management and any bilateral collaboration agreements with provincial governments. This is a new point of analysis for both public administrators and nonprofit network leaders. The alignment of network governance in four structural dimensions is analyzed, as are parallel nonprofit policy network structures within provincial governments and select nonprofit policy outcomes. RÉSUMÉ Au Canada, les gouvernements provinciaux et les dirigeants de réseaux à but non lucratif se sont engagés dans une « troisième vague » de consultations, dialogues politiques et stratégies d’alignement politique. Inexplorée jusqu’à ce jour est la manière dont les réseaux d’action publique à but non lucratif sont gouvernés et structurés. Pourtant, la structure des réseaux pourrait avoir des implications importantes pour la gestion politique et tout accord de collaboration bilatérale avec les gouvernements provinciaux. Il s’agit ici d’un nouveau sujet d’analyse, tant pour les administrateurs publics que pour les dirigeants de réseaux sociaux. Cet article évalue la division en quatre dimensions structurales de la gouvernance des réseaux, les structures parallèles des réseaux d’action publique à but non lucratif au sein des gouvernements provinciaux et certains résultats émanant de politiques à but non lucratif.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".