MétaCan
Menu
Back to cohort
Record W2997674631 · doi:10.12928/jehcp.v8i4.12962

Adapting the Child and Youth Resilience Measure-Revised for Indonesian Contexts

2019· article· en· W2997674631 on OpenAlexaff
Ihsana Sabriani Borualogo, Philip Jefferies

Bibliographic record

VenueJournal of Educational Health and Community Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
FundersUniversitas Islam Bandung
KeywordsIndonesianMeasure (data warehouse)Adaptation (eye)Resilience (materials science)Reliability (semiconductor)Context (archaeology)PsychologyPsychological resilienceValidityCronbach's alphaFocus groupDevelopmental psychologySocial psychologyGeographyComputer scienceSociologyPsychometricsAnthropologyData mining

Abstract

fetched live from OpenAlex

This study describes the adaptation of the Child and Youth Resilience Measure-Revised (CYRM-R) for use in Indonesia. The process of adaptation involved several steps. The first step was translating and back-translating the measurement. The next step was conducting focus groups to explore the legibility of the translated measure. After this, the validity and the reliability of the translated version was tested, as well as an exploration of data. Samples were130 elementary school children (57.7% female) aged 10-13. Data were collected in 2 randomly chosen elementary schools in Kota Bandung. The analyses confirmed the validity and reliability of the measure (alpha = .902). The results indicated that the CYRM-R had been adapted successfully and is a robust measure for exploring the social-ecological resilience of children and youth in Indonesia. The CYRM-R can be used for research and practice in the Indonesian context. Keywords: resilience; child; measurement; cross-cultural; CYRM-R; Indonesia

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.443
Teacher spread0.382 · 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 teacher head, 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

Citations24
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Educational Health and Community PsychologySame topicResilience and Mental HealthFrench-language works237,207