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Religion, ethnicity, and the secular world

2014· article· en· W2137798559 on OpenAlexaff
Paula Montero

Bibliographic record

VenueVibrant Virtual Brazilian Anthropology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society in Latin America
Canadian institutionsNational Association of Friendship Centres
Fundersnot available
KeywordsEthnic groupMulticulturalismNationalityPoliticsGender studiesRelation (database)Secular stateSociologyState (computer science)ConventionPolitical scienceSecularismSocial scienceLawAnthropologyImmigration

Abstract

fetched live from OpenAlex

This paper explores the contrastive, or even contradictory, relations established between 'religions' and 'ethnicities' and what is by convention called the secular world in the conception of contemporary multicultural and post-secular democracies. When and why are 'religions' and 'ethnicities' perceived as a challenge to the political system? We draw on the literature that addresses the challenges posed by the growing presence of Muslim populations in Europe in order to analyze the confrontation in Brazil between Neo-Pentecostal and Afro-Brazilian groups. Our purpose is to understand why, differently from the European conflict, in which Muslim minorities are perceived as a simultaneously ethnic and religious challenge, conflict in Brazil occurs in a doubly inverted relation. Afro-Brazilian religions have built a positive relation to Brazilian nationality and have been acknowledged as religions by the State. In contrast, Neo-Pentecostal religions, although legally recognized, are weakly connected to Brazilian nationality.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.010
GPT teacher head0.306
Teacher spread0.295 · 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 designQualitative
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

Citations2
Published2014
Admission routes1
Has abstractyes

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