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Record W4293154316 · doi:10.3986/dd.2016.2.03

The assessment of cultures and the autonomy of communities

2016· article· en· W4293154316 on OpenAlexaff
Avigail Eisenberg

Bibliographic record

VenueTwo Homelands · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of VictoriaQueen's University
Fundersnot available
KeywordsCultural rightsMulticulturalismIndigenous rightsPolitical sciencePoliticsCitizenshipAutonomyIndigenousLiberalismDemocracyScholarshipSociologyMinority rightsHuman rightsLawGender studiesEnvironmental ethicsFundamental rights

Abstract

fetched live from OpenAlex

Cultural rights are one response to the mistreatment of minorities by dominant groups. Their protection has become a litmus test for the liberal nature of democratic states. At the same time, criticisms of cultural rights abound in scholarship and popular discourse. These include concerns that cultural rights distort and essentialize culture, that cultural protections shield gender discrimination, and that cultural rights legitimize a false narrative about the capacity of Western states to act justly towards subjugated minorities and, in particular, indigenous peoples. The question addressed here is whether the protection of cultural rights, as defended by Kymlicka in his 1989 book Liberalism, Community and Culture, is still an important project today in light of these criticisms and against the background of recent political circumstances which find some political leaders distancing themselves from multiculturalism and where, once again, cultural difference is used to exclude minorities from the full rights of citizenship.

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)0.010
metaresearch head score (Gemma)0.016
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: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.077
Scholarly communication0.0130.010
Open science0.0010.012
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.382
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 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
Published2016
Admission routes1
Has abstractyes

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