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Culture and Equal Treatment

2025· book-chapter· en· W4415387941 on OpenAlexaboutno aff
Burke A. Hendrix

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsState (computer science)Consistency (knowledge bases)Character (mathematics)Cultural diversityInequality

Abstract

fetched live from OpenAlex

Abstract This chapter examines elements of Canadian law that require Native peoples to state the character of their cultural difference in highly specific terms, and argues that this constitutes an unreasonable standard. While human communities differ in what they value, these divergences are hard to articulate clearly even when those involved understand them well, which is rarely the case. It argues instead for an open-ended standard that accepts that Native peoples were historically different and have had very different experiences of political power. It argues that Native cultural rights represent an exercise of distributive consistency in conditions where states have neither desire nor capacity for neutrality. The chapter focuses on land and territory as spaces for culturally inflected political choices to be carried out over both the short and long term.

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)0.002
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.391
Threshold uncertainty score0.777

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.028
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.087
GPT teacher head0.359
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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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