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Fostering family resiliency: a review of the key protective factors

2008· review· en· W1997298531 on OpenAlexaff
Karen Benzies, Richelle Mychasiuk

Bibliographic record

VenueChild & Family Social Work · 2008
Typereview
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychological interventionPsychologyProtective factorPeer supportFoundation (evidence)Developmental psychologyMedicinePsychiatryPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT The aim of this integrative review was to identify the protective factors that contribute to family resiliency. Families are comprised of individuals who interact across levels in a socio‐ecological system. Family resiliency does not develop through evasion of risk, but through successful application of protective factors to engage in adverse situations and emerge from them stronger. In an effort to move away from pathological labelling, this review provides a foundation for strength‐based family interventions. Thirteen peer‐reviewed databases were searched for articles and information regarding family resiliency. Careful review yielded 24 protective factors that foster resiliency across three distinct but interactive levels: individual, family and community. The protective factors identified in this review of the literature offer an excellent starting point for development of clinical interventions to support family resiliency.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.102
GPT teacher head0.412
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations491
Published2008
Admission routes1
Has abstractyes

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