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Record W2122062477 · doi:10.1093/bjsw/bcl343

Resilience across Cultures

2006· article· en· W2122062477 on OpenAlexafffund
Michael Ungar

Bibliographic record

VenueThe British Journal of Social Work · 2006
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
FundersSocial Sciences and Humanities Research Council of CanadaNova Scotia Health Research Foundation
KeywordsContext (archaeology)Resilience (materials science)Psychological resiliencePsychological interventionPsychologyDevelopmental psychologySocial psychologySociologyGeography

Abstract

fetched live from OpenAlex

Findings from a 14 site mixed methods study of over 1500 youth globally support four propositions that underlie a more culturally and contextually embedded understanding of resilience: 1) there are global, as well as culturally and contextually specific aspects to young people’s lives that contribute to their resilience; 2) aspects of resilience exert differing amounts of influence on a child’s life depending on the specific culture and context in which resilience is realized; 3) aspects of children’s lives that contribute to resilience are related to one another in patterns that reflect a child’s culture and context; 4) tensions between individuals and their cultures and contexts are resolved in ways that reflect highly specific relationships between aspects of resilience. The implications of this cultural and contextual understanding of resilience to interventions with at-risk populations 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)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0050.004
Scholarly communication0.0050.004
Open science0.0010.011
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.378
Teacher spread0.365 · 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 designQualitative
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

Citations1,855
Published2006
Admission routes2
Has abstractyes

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