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Record W1966146171 · doi:10.1111/jmft.12124

Varied Patterns of Family Resilience in Challenging Contexts

2015· review· en· W1966146171 on OpenAlexaff
Michael Ungar

Bibliographic record

VenueJournal of Marital and Family Therapy · 2015
Typereview
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsResilience (materials science)PsychologyFamily resilienceSocial psychologyDevelopmental psychologyPsychological resilienceMaterials science

Abstract

fetched live from OpenAlex

While we know much about patterns of family resilience, most of our research and clinical discussion has focused on microsystemic, intrafamilial protective processes. We have far fewer maps of the bidirectional interactions between families and other systems that contribute to successful family adaptation in challenging contexts. The purpose of this article is to address this gap in knowledge and present a map of family resilience that is both systemic and contextually and culturally responsive. Seven specific patterns of family resilience are reviewed. Combined, they account for the varied adaptational patterns families use to nurture and sustain resilience. The article concludes with reflection on how we can assess family resilience and the application of this map to family therapy.

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)0.003
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.108
GPT teacher head0.429
Teacher spread0.321 · 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
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

Citations98
Published2015
Admission routes1
Has abstractyes

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