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Record W2026686118 · doi:10.2466/pr0.100.3.963-978

A Psychometric Assessment of the Self-Reported Youth Resiliency: Assessing Developmental Strengths Questionnaire

2007· article· en· W2026686118 on OpenAlexaff
Tyrone Donnon, Wayne Hammond

Bibliographic record

VenuePsychological Reports · 2007
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyDevelopmental psychologyConstruct (python library)Clinical psychologyConstruct validityPsychometrics

Abstract

fetched live from OpenAlex

As opposed to the problem-based approach of dealing with specific at-risk behaviors, the objective of the self-reported Youth Resiliency: Assessing Developmental Strengths questionnaire is to provide a statistically sound and research-based approach to understanding the factors that contribute to the development of adolescent resiliency. The study of protective factors, or the more recent attempts at conceptualizing the phenomena of individual resiliency, has been prevalent in the social and health sciences research for decades. In this study, the psychometric characteristics of the Youth Resiliency questionnaire, based on a large urban sample of Grades 7 to 9 adolescents (N= 2,291), are presented. The findings from this study present a potential framework for understanding the construct and function of resiliency as it pertains to both the extrinsic and intrinsic factors of adolescent development.

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)0.006
metaresearch head score (Gemma)0.012
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 score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.051
GPT teacher head0.452
Teacher spread0.401 · 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

Citations69
Published2007
Admission routes1
Has abstractyes

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