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Record W2920504598

CONSTITUTIONAL WORKAROUNDS : SENATE REFORM AND OTHER EXAMPLES

2011· article· en· W2920504598 on OpenAlexaboutno aff
Robert E. Hawkins

Bibliographic record

VenueThe Canadian Bar Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsWorkaroundConstitutionFederalismPolitical scienceLegislationParliamentLawConstitutional lawCLARITYPoliticsConstitutional amendmentGovernment (linguistics)PolityPublic administration
DOInot available

Abstract

fetched live from OpenAlex

The process for amending Canada’s constitution is complex and difficult. As a result, “back door” routes for realizing change of a constitutional nature have been adopted. These “workarounds” include “formula shopping,” where amendment procedures requiring a lesser measure of provincial consent are adopted; ordinary legislation, where no provincial consent is sought at all; and hortatory declarations, where mere statements purport to define a government’s position with respect to particular constitutional issues. Workarounds in areas such as Senate reform, fixed date election laws, secession and clarity acts, and regional vetoes, along with declarations dealing with special status for Quebec, the federal spending power, and prorogation of Parliament, will be examined. Key to the constitutional validity of these workarounds is whether they bind the actions of relevant political actors, as opposed to being merely advisory or consultative. At stake is the interplay between two fundamental constitutional values: flexibility, which permits the constitution to adapt to changing societal realities; and federalism, which requires a meaningful degree of provincial consent for significant constitutional change.

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)0.031
metaresearch head score (Gemma)0.044
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: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.647

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.009
Science and technology studies0.0240.018
Scholarly communication0.0090.005
Open science0.0030.006
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0110.001

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 head0.096
GPT teacher head0.296
Teacher spread0.200 · 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
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

Citations2
Published2011
Admission routes1
Has abstractyes

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