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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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0150.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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