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Record W2905367078 · doi:10.1002/pchj.256

A cross‐cultural validation of the Resiliency Scale for Young Adults in Canada and China

2018· article· en· W2905367078 on OpenAlexaffabout
Claire A. Wilson, Rachel A. Plouffe, Donald H. Saklofske, Gonggu Yan, David Nordstokke, Sandra Prince‐Embury, Yan Gao

Bibliographic record

VenuePsyCh Journal · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of CalgaryWestern University
Fundersnot available
KeywordsConfirmatory factor analysisMeasurement invariancePsychologyInternal consistencyScale (ratio)Cross-cultural studiesStructural equation modelingSample (material)Cross-culturalAnxietyClinical psychologyChinaFlourishingDevelopmental psychologySocial psychologyPsychometricsStatisticsMathematics

Abstract

fetched live from OpenAlex

The current study reports on a cross-cultural validation of the recently developed Resiliency Scale for Young Adults (RSYA) with two samples consisting of 617 Canadian university students and 651 Chinese university students. Confirmatory factor analysis, tests of cultural invariance, and correlations with relevant individual difference variables were conducted as tests of validity. In the Chinese sample, confirmatory factor analysis supported the factor structure of the RSYA and internal consistency reliabilities for the three factors and 10 facets were good-to-excellent. Cultural and gender invariance were supported. Correlations with depression, anxiety, stress, flourishing, and life satisfaction were also in the expected direction in the Chinese sample. These findings provide additional support for the RSYA as a reliable and valid measure of personal resiliency for Chinese young adults. Findings support the three-factor model of personal resiliency in both Canadian and Chinese young adults, as well as cultural and gender invariance. The robustness of this model has implications for assessing and developing resiliency cross-culturally.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.262
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.379
Teacher spread0.363 · 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
Published2018
Admission routes2
Has abstractyes

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