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Record W2765697067 · doi:10.1177/0734282917740017

Resiliency Across Cultures: A Validation of the Resiliency Scale for Young Adults

2017· article· en· W2765697067 on OpenAlexaffabout
Claire A. Wilson, Rachel A. Plouffe, Donald H. Saklofske, Annamaria Di Fabio, Sandra Prince‐Embury, Sarah E. Babcock

Bibliographic record

VenueJournal of Psychoeducational Assessment · 2017
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsWestern University
Fundersnot available
KeywordsGeneralizability theoryPsychologyFacet (psychology)Confirmatory factor analysisScale (ratio)PersonalityBig Five personality traitsMeasurement invarianceSample (material)TraitInternal consistencyReliability (semiconductor)Structural equation modelingMetric (unit)PsychometricsDevelopmental psychologyClinical psychologySocial psychologyStatistics

Abstract

fetched live from OpenAlex

This study presents a cross-cultural validation of the recently developed Resiliency Scale for Young Adults (RSYA) with a sample of 289 Canadian university students and 259 Italian university students. The RSYA demonstrated good internal consistency across the two samples and acceptable retest reliability for the Canadian sample. Confirmatory factor analysis supported the three-factor, 10-facet structure of the RSYA, and comparison of the two country samples found metric invariance. As expected, positive correlations also emerged between resiliency and trait emotional intelligence in both samples. Finally, correlations with personality variables were explored in both samples. The present findings provide further support for the RSYA as a valid and reliable measure of personal resiliency for both Canadian and Italian young adults, and for the cross-cultural generalizability of the three-factor model of personal resiliency upon which it is based.

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)0.008
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 score0.215
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
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 head0.031
GPT teacher head0.508
Teacher spread0.477 · 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

Citations28
Published2017
Admission routes2
Has abstractyes

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