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Record W112316523

Acculturation as a predictor of depressive symptoms and life satisfaction among older Iranian immigrants in Canada

2011· dissertation· en· W112316523 on OpenAlexaboutno aff
Amir Moztarzadeh

Bibliographic record

VenueSummit (Simon Fraser University) · 2011
Typedissertation
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsAcculturationImmigrationLife satisfactionDepressive symptomsPsychologyClinical psychologyGerontologyMedicinePsychiatryAnxietyPolitical scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Limited acculturation of older ethnic immigrants in Canada may adversely impact their psychological well-being. When older adults are equipped with effective means of communication and are familiarized with the services and resources of their host country, they can expand their networks to foster service use and buffer them against isolation. As the existing literature suggests, there could be an association between health behaviour and acculturation. For this thesis, it was hypothesized that less acculturated Iranian-born older adults in Canada experience reduced psychological well-being. Demographic characteristics of this population also may account for variability in both acculturation and indicators of mental health; these were also examined as predictors of psychological well-being thesis. The results of this thesis indicated that acculturation predicts life satisfaction but not depressive symptoms among older Iranian immigrants residing in Metro Vancouver.

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)0.000
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 score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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