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Record W2886865847 · doi:10.7202/1050503ar

Re-Making Kinship. From Community to Family

2018· article· en· W2886865847 on OpenAlexaffvenue
Jessica Roda

Bibliographic record

VenueThéologiques · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsMcGill University
Fundersnot available
KeywordsKinshipFictive kinshipSociologyPhenomenonIdentity (music)GenealogyEmbodied cognitionGender studiesAnthropologyEthnologyAestheticsHistoryEpistemology

Abstract

fetched live from OpenAlex

The Sephardic Jews living in France, who use Judeo-Spanish as their heritage language, are an assimilated diasporic group that has witnessed war, assimilation and marginalization. With the increase in genealogical research in Western Society, many Sephardim have experienced a process of revitalization of memory through kin relations with people of similar descent. This complex revitalization takes form within the structure of a community cultural centre which acts as a place for re-making kinship thanks to the emotional experience of sharing a specific musical heritage. This phenomenon forces us to examine the tension between « traditional » kinship systems — embodied in the matrilineal bloodline in the case of halakhic Jewish identity — and symbolic kinship anchored in the idea of a « chosen family », to rethink kinship as a mixture between biology and culture, as well as to reconsider current anthropological debates on religion thought beyond the strict religious practices.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0090.012
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.319
GPT teacher head0.469
Teacher spread0.151 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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