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Record W2561027834 · doi:10.52324/001c.8031

Regional Inequality and Decentralized Governance: Canada’s Provinces

2016· article· en· W2561027834 on OpenAlex
M. Rose Olfert

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

VenueReview of Regional Studies · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInequalityContext (archaeology)Government (linguistics)Constraint (computer-aided design)Corporate governanceRelevance (law)Convergence (economics)PoliticsPublic policyPublic economicsEconomicsPolitical scienceDevelopment economicsRegional scienceEconomic growthGeography

Abstract

fetched live from OpenAlex

Regional scientists commonly concern themselves with topics involving regional inequalities—why they occur and persist, how inequality may be reduced or what exacerbates it, and the impact of policy interventions. Regional nequalities fuel our research and its policy relevance. For most of us, these investigations are in the context of exogenously defined “regions,” with political and administrative boundaries originating in a decentralized government context. The regions that are our units of analysis seldom reflect economic realities, yet their boundaries, once drawn, are very persistent and to a large extent determine the degree to which inequalities may be reduced over time, either through private decisions or through government policy. This paper offers a descriptive illustration of fundamental differences among Canada’s provinces as a potential constraint on the possibility of convergence over time, interregional migration responses, and the impacts of an explicit national government equalization.

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)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.838
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.067
GPT teacher head0.269
Teacher spread0.202 · 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