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Record W4402553924 · doi:10.1093/publius/pjae034

Between Decentralization and Asymmetry: Explaining Preferences toward the Division of Power in Canada

2024· article· en· W4402553924 on OpenAlexafffundabout
Philippe Chassé, Olivier Jacques, Colin Scott

Bibliographic record

VenuePublius The Journal of Federalism · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsConcordia UniversityUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsDecentralizationFederalismPoliticsPolitical scienceContext (archaeology)Identity (music)Political mobilizationPower (physics)Public administrationPolitical economySociologyGeographyLaw

Abstract

fetched live from OpenAlex

Abstract In most federations, the division of power between central and subnational governments represents an important cleavage dividing voters and structuring party systems. Yet we lack a robust body of research regarding individuals’ preferences for different forms of devolved decision-making such as decentralization and asymmetrical federalism. This article contributes to this research agenda by analyzing the effects of identity and grievances on public opinion toward the division of powers in Canada. Leveraging four waves of the Confederation of Tomorrow survey, we find that respondents who identify predominantly with their province are more likely to prefer decentralization and asymmetrical federalism, whereas those who hold grievances against the federation prefer decentralization. Studying provincial variations in the impact of our main variables, we point to the role of the political context by showing that in certain provinces, the political mobilization of grievances strengthens the relationship between provincial identity and support for decentralization.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.028
GPT teacher head0.285
Teacher spread0.257 · 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

Citations7
Published2024
Admission routes3
Has abstractyes

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Same venuePublius The Journal of FederalismSame topicPolitical Systems and GovernanceFrench-language works237,207