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Record W3122432038 · doi:10.29173/alr2613

Rethinking the Instrumental Rationality Principles of Fundamental Justice

2020· article· en· W3122432038 on OpenAlexvenueaboutno aff
Colton Fehr

Bibliographic record

VenueAlberta Law Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsRationalityEconomic JusticeEconomicsLaw and economicsEpistemologySociologyPhilosophyNeoclassical economics

Abstract

fetched live from OpenAlex

In Canada (Attorney General) v. Bedford, the Supreme Court of Canada fundamentally altered its approach to proving breaches of the instrumental rationality principles of fundamental justice. In response, commentators have charged that the Supreme Court’s new “individualistic” approach makes it too easy to prove a breach of the principles of fundamental justice. This is mainly a result of the Supreme Court’s expanded understanding of overbreadth, which now requires only that a law apply in an arbitrary manner to a single person. The problem with the Supreme Court’s new approach, however, is not necessarily with individualizing the analysis. Instead, upon revamping the instrumental rationality principles, the Supreme Court neglected to ask a more basic question: does the new conception of each principle still meet the requirements to qualify as a principle of fundamental justice? Although the arbitrariness and gross disproportionality principles are still integral to fundamental justice, I contend that the individualized conception of overbreadth has inadequate societal consensus to qualify as a principle of fundamental justice.

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)0.028
metaresearch head score (Gemma)0.022
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 score0.186
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0070.053
Scholarly communication0.0120.011
Open science0.0040.007
Research integrity0.0090.024
Insufficient payload (model declined to judge)0.0020.001

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 head0.108
GPT teacher head0.343
Teacher spread0.236 · 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
Published2020
Admission routes2
Has abstractyes

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