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Record W2175401153

Sur les Frontières de la Reconnaissance: Les Catégories Internes et Externes de l'Identité Collective

2006· article· fr· W2175401153 on OpenAlexaboutno aff
Michèle Lamont, Christopher A. Bail

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceEthnologyArtSociology
DOInot available

Abstract

fetched live from OpenAlex

Faisant appel aux etudes recentes portant sur la reconnaissance et l’identite sociale, nous analysons les changements dans la categorisation de l’identite collective des groupes stigmatises en Israel, en Irlande du Nord, au Quebec et au Bresil. Alors que la litterature sur la reconnaissance tend a presumer une opposition nette entre « nous » et « eux », l’analyse de la litterature empirique demontre la complexification et la multiplication des categories d’identite. Dans les quatre cas nous avons observe le processus de reconnaissance, en explorant les transformations de la signification des frontieres internes et externes de l’identite collective pour ses membres ainsi que pour ceux qui lui sont exterieurs. Nous soutenons que la nature conditionnelle de la reconnaissance devrait conduire les chercheurs a considerer non seulement les composantes normatives du conflit ethnique mais aussi, en leur accordant une importance particuliere, le langage et la categorisation qui fondent ce type de debat.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0080.026
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.085
GPT teacher head0.385
Teacher spread0.300 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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