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Federalism and Redistribution in Canada

2025· book-chapter· en· W4408729406 on OpenAlexaffabout
Keith Banting

Bibliographic record

VenueOxford University Press eBooks · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsQueen's University
Fundersnot available
KeywordsRedistribution (election)FederalismPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Abstract This chapter explores the relationship between federalism and redistribution in Canada. Comparative evidence confirms that the Canadian welfare state reduces inequality less than in many other contemporary democracies, and a longstanding debate has centered on whether Canada’s federal institutions are part of the reason. The chapter argues that the primary explanation for the limited redistributive role of the Canadian state is to be found in the political economy of the country. However, federal institutions do play a secondary role, constraining redistributive politics in several ways. The intensity of these constraints does evolve over time, reflecting shifts in prevailing policy agendas and the political coalitions driving them. Nonetheless, federalism undoubtedly raises the level of political energy and determination required to change the trajectory of social policy in the country.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.083
Threshold uncertainty score0.604

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0080.005
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.000

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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes2
Has abstractyes

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