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Record W2170143591 · doi:10.1177/1368430210370602

A multidimensional approach to identity: Religious and cultural identity in young Jewish Canadians

2010· article· en· W2170143591 on OpenAlexaffabout
Reeshma Haji, Richard N. Lalonde, Anna Durbin, Ilil Naveh-Benjamin

Bibliographic record

VenueGroup Processes & Intergroup Relations · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsUniversity of TorontoYork UniversityLaurentian University
Fundersnot available
KeywordsReligious identitySalience (neuroscience)Cultural identityJudaismJewish identityIdentity (music)PsychologySocial psychologyIdentity formationSociologyGender studiesReligiositySelf-conceptTheologyFeeling

Abstract

fetched live from OpenAlex

This study used an online questionnaire to explore the relations among different dimensions of religious and cultural Jewish identity in young Canadian adults ( N = 258). We investigated the extent to which three aspects of Jewish identity—religious identity, cultural identity, and identity salience— predicted openness to interfaith relationships and sociopolitical attitudes related to Israel. Results showed that compared to participants who self-identified as cultural Jews, those who self-identified as religious Jews or as both religious and cultural Jews scored higher on measures of cultural and religious identification. Moreover, relative to culturally identified Jews, religious and religious/cultural Jews were less open to interfaith relationships, endorsed more right-wing political attitudes with respect to Israel’s foreign policy, and reported that their Jewish identity was more salient than their Canadian identity in identity-relevant situations. Similarly, relative to Jews of other denominations, Orthodox Jews reported higher levels of Jewish identification, greater salience of their Jewish identity, and advocated more right-wing political views.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.012
GPT teacher head0.289
Teacher spread0.277 · 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 designObservational
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

Citations19
Published2010
Admission routes2
Has abstractyes

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