MétaCan
Menu
Back to cohort
Record W6980081802

Attempting to Expand Resilience to Policies: A Daunting Task and a Good Start [Review of the book Resilience in Children, Families, and Communities: Linking Context to Practice and Policy]

2005· article· en· W6980081802 on OpenAlexaboutno aff

Bibliographic record

VenueCornerstone (Minnesota State University, Mankato) · 2005
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)Context (archaeology)Task (project management)SPARK (programming language)Action (physics)Intervention (counseling)Psychological resilience
DOInot available

Abstract

fetched live from OpenAlex

"Resilience" is a word that is frequently used, but what does it mean, and how does it affect our children, families, and communities? That is precisely the topic of Resilience in Children, Families, and Communities: Linking Context to Practice and Policy (see record 2005-04214-000). This book, which is based on presentations at the 32nd Annual Banff International Conference on Behavioural Science (March 2000, Banff, Alberta, Canada), explores what is known about resilience and how that information can be used to intervene at levels beyond individual children. The reviewer concludes that this book is exciting in that it represents a call to action for those of us in resilience research, prevention and intervention efforts, and public policy to work together to use all of our expertise to make changes in our society, communities, and agencies to support children and their families. The reviewer hopes this book will spark more effective communication and collaboration in supporting resilience in the macro- and mesosystems in which youth live. Perhaps this fresh approach will result in a future volume in which authors may build on this text to elaborate on the effectiveness of empirically based, resilience-oriented community programs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.313
Teacher spread0.298 · 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.

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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCornerstone (Minnesota State University, Mankato)Same topicResilience and Mental HealthFrench-language works237,207