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Record W2605732432 · doi:10.1017/s0008423915000190

Power to the People? The Impacts and Outcomes of Energy Consultations in Saskatchewan and Nova Scotia

2015· article· en· W2605732432 on OpenAlexaffabout
Linsay Martens, Kathleen McNutt, Jeremy Rayner

Bibliographic record

VenueCanadian Journal of Political Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversity of ReginaUniversity of Saskatchewan
Fundersnot available
KeywordsNova scotiaLegitimacyCollaborative governanceCorporate governancePublic administrationPolicy learningPower (physics)Political sciencePublic policyPublic engagementPublic relationsSociologyEconomicsComputer sciencePoliticsManagementLaw

Abstract

fetched live from OpenAlex

Abstract Like other policy subsectors, power generation has been affected by the governance changes of the last two decades, including a shift to more collaborative state-society relations. Collaborative governance implies new kinds of public engagement designed to provide both input legitimacy, through the involvement of a broader range of actors in policy design, and output legitimacy, through enhanced feedback and policy learning. This paper compares the impact of “governance-driven engagement” in the power generation subsectors in Nova Scotia and Saskatchewan, arguing that engagement increased the complexity of the policy mix in the subsector without succeeding in providing better feedback and learning. The paper notes a recent trend towards more expert-driven and less collaborative processes, as both provinces struggled to rationalize and simplify power generation policy goals and instruments.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.325
Teacher spread0.301 · 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".

Quick stats

Citations10
Published2015
Admission routes2
Has abstractyes

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