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Record W1590894868 · doi:10.18357/ijcyfs122010670

Developmental Pathways Towards Crime Prevention: Early Intervention Models

2010· article· en· W1590894868 on OpenAlexaffvenueabout
Mike Boyes, Joseph P. Hornick, Nancy Ogden

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPanacea (medicine)Intervention (counseling)PsychologyStyle (visual arts)Span (engineering)Developmental psychologyMedicineHistoryPsychiatryEngineering

Abstract

fetched live from OpenAlex

In examining the role of early intervention in children’s social development, the authors discuss the results of five broad-based intervention programs based on the Healthy Families model originated in the State of Hawaii. These programs were directed toward families at moderate levels of risk when dealing with the arrival their first child and were situated in Charlottetown, Prince Edward Island, Whitehorse, Yukon, and at three sites in Edmonton, Alberta. The authors state that their experiences with this project have led them to question a number of traditional assumptions regarding past theory and research in this area as it pertains to crime prevention. More specifically, they discuss how the developmental model helped to identify the various developmental pathways of positive change that were being demonstrated by families in the Healthy Families Program sites. They agree with other researchers that early childhood intervention is viewed most appropriately as an individualized strategy and not as a developmental panacea.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0020.008
Scholarly communication0.0060.006
Open science0.0030.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.067
GPT teacher head0.340
Teacher spread0.273 · 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

Citations2
Published2010
Admission routes3
Has abstractyes

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