Policy capacity: A conceptual framework for understanding policy competences and capabilities
Bibliographic record
Abstract
Abstract Although policy capacity is among the most fundamental concepts in public policy, there is considerable disagreement over its definition and very few systematic efforts try to operationalize and measure it. This article presents a conceptual framework for analysing and measuring policy capacity under which policy capacity refers to the competencies and capabilities important to policy-making. Competences are categorized into three general types of skills essential for policy success—analytical, operational and political—while policy capabilities are assessed at the individual, organizational and system resource levels. Policy failures often result from imbalanced attention to these nine different components of policy capacity and the conceptual framework presented in the paper provides a diagnostic tool to identify such capacity gaps. It offers critical insights into strategies able to overcome such gaps in professional behaviour, organizational and managerial activities, and the policy systems involved in policy-making.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.003 | 0.032 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".