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Record W2896136361

Engagement with Human Rights by Administrative Decision-Makers: A Transformative Opportunity to Build a More Grassroots Human Rights Culture

2017· article· en· W2896136361 on OpenAlexaboutno aff
Dan Moore

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsGrassrootsHuman rightsDiscretionJurisprudencePolitical scienceInternational human rights lawCharterRedressLaw and economicsDemocracyLawPublic relationsPublic administrationSociology
DOInot available

Abstract

fetched live from OpenAlex

Trends in public law jurisprudence increasingly require administrative decision-makers to engage with complex human rights concepts in exercising their discretion. This includes not only the Charter but also international human rights sources. The engagement with human rights that is expected of administrative decision-makers is demanding: it is broad in terms of the concepts and sources that could be implicated, flexible in how the concepts could affect the decision, and rigorous in the required analysis. It will likely prove challenging for decision-makers, the people who are subject to their decisions, and the legal community in general.But there would be real benefits to meeting the challenge head-on. It will be argued that if this vision is realized, administrative proceedings will become an increasingly important venue for the contestation and interpretation of human rights. This amounts to a vision of a more grassroots and decentralized human rights culture in Canada, in which a wider range of individuals would have the opportunity to participate in structured, yet accessible, conversations about rights. Of course, realizing this vision in practice will be challenging. But if more voices are allowed to take part in debate about rights issues, democratic shortcomings in our rights culture could be rectified, and Canada’s human rights jurisprudence could benefit from unexpected innovations.

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)0.091
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.297
Threshold uncertainty score0.634

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0430.152
Scholarly communication0.0610.020
Open science0.0050.026
Research integrity0.0140.027
Insufficient payload (model declined to judge)0.0080.002

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 head0.044
GPT teacher head0.388
Teacher spread0.344 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicCriminal Law and EvidenceFrench-language works237,207