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Record W2521448919 · doi:10.1007/s13644-016-0265-2

Socioeconomic Status and Religious Beliefs among U.S. Latinos: Evidence from the 2006 Hispanic Religion Survey

2016· article· en· W2521448919 on OpenAlexaff
Jong Hyun Jung, Scott Schieman, Christopher G. Ellison

Bibliographic record

VenueReview of Religious Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProsperitySocioeconomic statusMiracleGeneral Social SurveyOddsSurvey data collectionSocial psychologyPsychologyReading (process)GospelSociologySociology of religionDemographyReligious studiesTheologyLogistic regressionPolitical scienceSocial scienceMedicinePhilosophyLaw

Abstract

fetched live from OpenAlex

This study examines how socioeconomic status is related to beliefs about the prosperity gospel and miracles among U.S. Latinos. Further, it investigates how religious involvement moderates this relationship. In analyses of data from the 2006 Hispanic Religion Survey (N = 3143), we find that higher levels of education and income are independently associated with lower likelihood of endorsing the prosperity gospel. However, the negative association between education and the likelihood of holding prosperity gospel beliefs is weaker among those Latinos who read scriptures frequently. In addition, although neither education nor income is directly related to miracle beliefs, their influence does depend on the frequency of scripture reading. For example, income is positively associated with the odds of endorsing miracle beliefs only among Latinos who regularly read scripture; by contrast, income is negatively associated with those same odds when scripture reading is infrequent. We discuss the implications of these findings for theories about the ways that different dimensions of social stratification are related to religious beliefs.

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)0.004
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.078
GPT teacher head0.420
Teacher spread0.342 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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