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Record W2023774703 · doi:10.1111/0952-1895.00124

Rebuilding Policy Capacity in the Era of the Fiscal Dividend: A Report from Canada

2000· article· en· W2023774703 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGovernance · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsDalhousie University
Fundersnot available
KeywordsLegitimacyRestructuringGovernment (linguistics)PoliticsPublic administrationFiscal capacityEconomic policyFiscal policyEconomicsPolitical scienceFinanceLawMacroeconomics

Abstract

fetched live from OpenAlex

After two decades of focusing on deficit reduction and restructuring of operations, governments in many areas of the world are once again contemplating new policies and expenditures. In Canada, where budgetary surpluses have recently replaced deficits, the federal government has been asking whether it still has the capacity to make informed choices about new programs. This article examines Canada’s recent efforts in rebuilding its policy capacity. It asks, first, to what extent and in what way was policy capacity originally lost. Second, it appraises the adequacy of new policy “networks,” consisting of think tanks, consultants and government officials, as “virtual replacements” for former government‐controlled advisory bodies, royal commissions, and in‐house policy units. Finally, it notes the relative absence of parliamentarians, and even the political executive, from capacity‐rebuilding activities, a deficiency that in the long run may undermine the legitimacy and effectiveness of such efforts.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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