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Record W1832873546 · doi:10.60082/2817-5069.1016

Inclusion, Voice, and Process-Based Constitutionalism

2013· article· en· W1832873546 on OpenAlexaffvenueabout
Colleen Sheppard

Bibliographic record

VenueOsgoode Hall law journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPolitical scienceConstitutionDemocracyFundamental rightsDutyConstitutional lawFraming (construction)CharterLawSociologyHuman rightsPolitics

Abstract

fetched live from OpenAlex

This article explores a growing emphasis on process issues in the elaboration of constitutional rights and freedoms, focusing on the Canadian Charter of Rights and Freedoms. In a diverse range of contexts, judges are framing constitutional rights and freedoms in terms of the processes and practices they require, rather than in terms of specific constitutionally mandated substantive outcomes. Thus, constitutional rights have been interpreted to require a duty to negotiate, a duty to consult, a duty to accommodate, and entitlements to participate in democratic governance. The growing emphasis on processes and practices is positive to the extent that it resonates with new understandings of social regulation in modern society, empowers institutional and social actors as change makers, and reduces reliance on the judiciary as interpreters of the substantive content of rights in diverse social and institutional contexts. Values of democratic participation, institutional and social transformation, empowerment, and self-governance also emerge with the shift towards processes and practices. And yet, it is also important to consider whether and to what extent a focus on processes and practices risks undermining constitutional protections.

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)0.021
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.079
Scholarly communication0.0150.016
Open science0.0020.011
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.290
Teacher spread0.273 · 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 designTheoretical or conceptual
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

Citations1
Published2013
Admission routes3
Has abstractyes

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