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Record W3191421169 · doi:10.1080/10508619.2021.1952370

Religious Identity Formation of Filipino Canadian Youth: Exploring Cluster Differences in Religiosity and Mental Health

2021· article· en· W3191421169 on OpenAlexafffundabout
Drexler L. Ortiz, Catherine L. Costigan

Bibliographic record

VenueInternational Journal for the Psychology of Religion · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReligiosityMental healthReligious identityIdentity (music)PsychologyEthnic groupPopulationHomogeneousCluster (spacecraft)Social psychologySociologyDemographyAnthropologyPsychiatry

Abstract

fetched live from OpenAlex

Individuals vary in how much exploration and commitment they invest in their identities, which results in different identity “statuses” across a population. Although the majority of Filipinos in Canada identify as Christian, how they each formed their religious identity status may be different, which would be important to understand given the strong relation between mental health and religiosity. Filipino Canadian youth (N = 181) aged 14 to 25 completed online questionnaires about their religious identity status, religiosity, and mental health. A cluster analysis was conducted on youth’s engagement with religious identity formation processes, and results revealed five religious identity statuses: Internalized, Ruminative Moratorium, Undifferentiated, Foreclosed, and Indifferent. Filipino youth with different religious identity statuses had distinct religious experiences and endorsed different levels of mental health. The study highlights the diverse religious experiences in a religiously homogeneous ethnic group which may have implications for mental health.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.001
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 head0.091
GPT teacher head0.403
Teacher spread0.312 · 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

Citations7
Published2021
Admission routes3
Has abstractyes

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