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Record W2243465984

Discretion and the Culture of Justice

2006· article· en· W2243465984 on OpenAlexaffabout
Lorne Sossin

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicOmbudsman and Human Rights
Canadian institutionsYork University
Fundersnot available
KeywordsDiscretionAdministrative discretionImpartialityPolitical scienceMulticulturalismEconomic JusticeContext (archaeology)State (computer science)Government (linguistics)Public relationsPublic servicePublic administrationLawSociology
DOInot available

Abstract

fetched live from OpenAlex

This paper analyzes the role of multiculturalism in the exercise of administrative discretion. Whether the setting is national security or social welfare eligibility, standards of justice rise or fall on the judgments of individual front-line decision-makers. Such decision-makers are the human face of the state. Against this contextual backdrop, this paper addresses a series of critical questions, including: To what extent is the exercise of discretion specifically, and the character of the administrative state more generally, determined by culture and identity? Will decision-makers in a representative public service treat members of their own communities differently than members of other communities? Administrative culture and culture of the society at large are deeply entangled in the exercise of discretion. The reasons for discretionary decisions, in other words, must grapple with and not sidestep the values, beliefs and administrative structures which underlie them. This approach is elaborated in the Canadian context, with particular emphasis on the policy of the federal government to achieve a multicultural public service and the development of impartiality and fairness standards in Canadian administrative law.

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)0.014
metaresearch head score (Gemma)0.021
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 score0.119
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0180.071
Scholarly communication0.0140.006
Open science0.0010.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.251
Teacher spread0.247 · 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

Citations3
Published2006
Admission routes2
Has abstractyes

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Same venueSSRN Electronic JournalSame topicOmbudsman and Human RightsFrench-language works237,207