Policy Capacity and Incapacity in Canada's Federal Government
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Governments, world-wide, are preoccupied with avoiding policy failure. A high level of policy capacity is considered one indicator of addressing this issue. Canada is typical of most countries where policy-related work tends to be centralized within its national capital city (Ottawa). There have been criticisms that on-the-ground perspectives are not conceded in policy decisions. Given the vast size and the decentralization of power, very little research has been dedicated to policy work conducted in its regions and whether it contributes to strengthening policy capacity. This article employs eight key hypotheses about contribution of Canadian regionally-based federal policy work to policy capacity based upon data derived from a national survey. A structural equation model (LISREL) is used to present the results. We find that regional-based policy work currently does little to enhance policy capacity. Policy work is divided along two distinct functional lines: traditional policy analysis and ‘street-level’ bureaucracy. The more engaging policy analysts belong to formal policy units which are a critical aspect of stronger policy capacity. The second factor contributing to policy capacity were attitudes towards the larger political arena.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it