Governmental policy capacity and policy work in a small place: Reflections on perceptions of civil servants in Prince Edward Island, Canada from a practitioner in the field
Bibliographic record
Abstract
The body of public administration literature is missing contributions from practitioners in the field. Emic or insider-led studies of public administration can act as powerful mechanisms to generate new knowledge. This article studies the relationship between place, perceptions and policy work by drawing on the author’s own public administration experience and interviews with civil servants. The results show that societal factors such as political culture and reduced anonymity associated with small place create challenges when developing public policy. However, expedited public engagement and problem identification were perceived by civil servants to be enhanced by a small context. This means that small place can be both limiting and beneficial for high levels of policy capacity. Overall, this article finds that geospatial factors such as smallness impact perceptions of policy work and capacity. Furthermore, this article finds that insider-led studies of public administration can indeed make important and unique contributions to the body of literature and are therefore deserving of more serious methodological consideration.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.027 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".