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Record W2118167612 · doi:10.1177/1558689811400607

Assessing Resilience Across Cultures Using Mixed Methods: Construction of the Child and Youth Resilience Measure

2011· article· en· W2118167612 on OpenAlexaff
Michael Ungar, Linda Liebenberg

Bibliographic record

VenueJournal of Mixed Methods Research · 2011
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMeasure (data warehouse)Resilience (materials science)MultimethodologyPsychologyQualitative researchPsychological resiliencePositive Youth DevelopmentQualitative propertyApplied psychologyDevelopmental psychologySocial psychologySociologyComputer scienceSocial sciencePedagogy

Abstract

fetched live from OpenAlex

An international team of investigators in 11 countries have worked collaboratively to develop a culturally and contextually relevant measure of youth resilience, the Child and Youth Resilience Measure (CYRM-28). The team used a mixed methods design that facilitated understanding of both common and unique aspects of resilience across cultures. Quantitative and qualitative stages to its development ensure the CYRM-28 has good content-related validity across research sites. Crossover comparison analyses of the findings from the quantitative administration of the pilot measure with 1,451 youth and qualitative interviews with 89 youth support the CYRM-28 as a culturally sensitive measure of youth resilience. The implications of this mixed methods approach to the development of measures for cross-cultural research are discussed.

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)0.022
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.004
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 head0.307
GPT teacher head0.614
Teacher spread0.307 · 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
GenreMethods

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

Citations726
Published2011
Admission routes1
Has abstractyes

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