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Record W2083442356 · doi:10.1080/13597560802223912

Intergovernmental Relations Post-devolution: Active Labour Market Policy in Canada and the United Kingdom 1996–2006

2008· article· en· W2083442356 on OpenAlexafffundabout
Donna E. Wood, Thomas R. Klassen

Bibliographic record

VenueRegional & Federal Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsYork University
FundersYork UniversityScottish Government
KeywordsDevolution (biology)Political scienceKingdomPublic administrationRegional policyGeographyLawArchaeology

Abstract

fetched live from OpenAlex

Devolution of active labour market policy has been pursued by both the Canadian and UK governments during the past decade and, as a result, new intergovernmental relationships have developed. These are compared, focusing in particular on relationships between the Government of Canada and the Government of the province of Alberta, and the UK Government and the Scottish Executive. The analysis concludes that intergovernmental relations and the workability of the intergovernmental relations system in the two countries are fundamentally different. This is due to distinct features in the structure of the state (the constitution, the number of sub-state governments and the asymmetry between them, how finances are shared, and how power is divided), and in the governing structure for active labour market policy (the degree of decentralization, the power of central government to act, the involvement of actors external to government, and the operation of the intergovernmental machinery) in each country. It is also due to the continued presence in the UK, during the period of this research, of two powerful forces of intergovernmental accommodation not found in Canada—a unitary party system and unified civil service.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.758

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0160.004
Scholarly communication0.0070.002
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.046
GPT teacher head0.316
Teacher spread0.270 · 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 designObservational
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

Citations6
Published2008
Admission routes3
Has abstractyes

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