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Record W1519110318 · doi:10.24908/fg.v10i1.4575

Book Review: Federalism and the Constitution of Canada

2013· article· en· W1519110318 on OpenAlexaffvenueabout
Jennifer Mussell

Bibliographic record

VenueFederal Governance · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsYork University
Fundersnot available
KeywordsFederalismConstitutionDual federalismJurisdictionPolitical scienceNew FederalismCooperative federalismGovernment (linguistics)LawPublic administrationSociologyPoliticsLinguistics

Abstract

fetched live from OpenAlex

In his recent book, Federalism and the Constitution of Canada, David E. Smith characterizes Canada’s federalism as existing on two planes. Horizontally, Canada consists of a territorial federalism- divided among ten provinces with equal jurisdiction and three territories, united by a common central government. Vertically, Canada is a cultural federation: two distinct nations, the English and the French, again connected by a common central government. Using this schema, Smith reevaluates some of the key questions in Canadian federalism. In particular, he analyses the relationship between Canada’s constitution and its variant of federalism. While Smith’s analysis provides a novel approach to the study of Canadian federalism, this review highlights some of the difficulties with his framework of dual federalism; in particular that his conception of cultural federalism is too rigid to accommodate Canada’s broad cultural composition.

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.700

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.020
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0240.004

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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
GenreReview

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

Citations0
Published2013
Admission routes3
Has abstractyes

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