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Record W4368347279 · doi:10.1093/publius/pjad014

<i>A Written Constitution for Quebec?</i> edited by Léonid Sirota and Richard Albert

2023· article· en· W4368347279 on OpenAlexaffabout
Andrew McDougall

Bibliographic record

VenuePublius The Journal of Federalism · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsUniversity of TorontoThe Scarborough Hospital
Fundersnot available
KeywordsConstitutionQueen (butterfly)FederalismClassicsMedia studiesSociologyArt historyHistoryLawPolitical sciencePolitics

Abstract

fetched live from OpenAlex

When the Premier of Quebec, François Legault, announced his intention as part of an overhaul of the province’s language laws to declare Quebec a “nation” in the Canadian constitution by amending the Quebec provincial constitution, the general consensus was that this would be constitutionally invalid. Regardless, there was enough ambiguity that it threw a light on the understudied relationship between the provincial and national constitutions in Canada. As the editors, Richard Albert and Léonid Sirota, note in the introduction, this and similar events have touched on a long-standing debate in Quebec as to whether or not its unwritten constitution should be codified, a subject also relevant to the constitutions of comparable substate polities and other Canadian provinces. Hence the book’s provocative title: A Written Constitution for Quebec? The answer is no. At least, it is difficult after reading this volume to come to any other conclusion. While that statement risks serving as a spoiler of sorts to a potential reader, fear not. Any scholar of Canada or Quebec’s constitutional politics would be well served to read this book regardless. Even if the destination is clear, this trip is well worth taking.

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)0.005
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: none
Teacher disagreement score0.952
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0060.004
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0770.013

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 head0.021
GPT teacher head0.287
Teacher spread0.267 · 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
Published2023
Admission routes2
Has abstractyes

Explore more

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