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Record W4387300664 · doi:10.32920/24208341

Perceptions of policy capacity: A case study of the Prince Edward Island public service using theory and practice

2023· preprint· en· W4387300664 on OpenAlexaboutno aff
Bobby Thomas Cameron

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsPublic administrationGovernment (linguistics)Public policyPoliticsInsiderPublic servicePolitical scienceEmic and eticCivil servantsPopulationSociologyPublic relationsManagementEconomicsLaw

Abstract

fetched live from OpenAlex

This study explores Prince Edward Island (PEI) provincial public servants’ perceptions of policy capacity using interviews with deputy ministers, directors, and managers and a survey administered to all public servants at one department. As a practicing public servant in Canada’s smallest province, PEI, with a population of 152,021 and a provincial civil service made up of 2,174 staff members, in this study I bring an emic or inside-government perspective to the study of policy capacity and show the benefits of adopting a single case study approach as opposed to a comparative method. The research questions which drove this study were: (1) What are PEI public servants’ perceptions of the general nature of policy processes and policy work in PEI and why? (2) How have PEI public servants constructed analytical, operational, and political policy capacity at the systemic, organizational, and individual levels? (3) What have PEI public servants observed in practice regarding analytical, operational, and political policy capacity at the systemic, organizational, and individual levels? and (4) What are PEI public servants’ recommendations for improving policy capacity and why? This study represents the first time that Government of PEI policy capacity has been subject to rigorous, scholarly inquiry as well as the first time that a practicing public administrator has adopted an explicitly emic or insider-approach to study policy capacity. This study therefore provides a blueprint for public administrators in other Canadian jurisdictions to study policy capacity, and fills a gap in knowledge of provincial government policy capacity in PEI. Inductive analysis resulted in the development of the islandness of public policy concept, policy leadership theory, the policy-driven organization concept, and recommendations for sub-national governments to improve policy capacity. Deductive analysis using a nested theoretical model of policy capacity resulted in empirical findings related to the Government of PEI’s analytical, operational, and political capacity at the individual, organizational, and systemic levels. First, the study’s focus on Government of PEI policy capacity heeds policy scholars who have noted that there are gaps in knowledge about how sub-national provincial governments in Canada view policy work and policy capacity. The literature review showed that similar studies of a provincial government’s policy capacity and policy work have been completed in British Columbia, Saskatchewan, and Quebec but not in PEI. Second, the study found that Government of PEI policy capacity is impacted by the smallness, isolation, reduced physical distance, and reduced anonymity associated with islandness; this has implications in terms of how policy processes and policy work unfolds in government. Third, historical and current austerity practices and discourses have resulted in challenges for the development of effective provincial public policy in this jurisdiction. Finally, grounded in the practice-based experiences of public servants, this study makes several recommendations for sub-national provincial governments to consider to improve policymaking abilities and policy work. For academics, this study recommends that future research continues to develop theories and empirical typologies of policy work which are applicable to both policy analysts and non-policy staff. Doing so will expand and deepen knowledge on the complex web of bureaucratic policy work which is required to develop public policy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0180.008
Scholarly communication0.0040.003
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.237
GPT teacher head0.486
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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