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Record W2556519978 · doi:10.1097/fch.0000000000000129

Systematic Braiding of 2 Evidence-Based Parent Training Programs

2016· article· en· W2556519978 on OpenAlexaff
Kate Guastaferro, Katy Miller, Jenelle R. Shanley Chatham, Daniel J. Whitaker, Kate McGilly, John R. Lutzker

Bibliographic record

VenueFamily & Community Health · 2016
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcGill University
FundersNational Institute on Drug Abuse
KeywordsCurriculumIntervention (counseling)Parent trainingMedical educationPsychologySystematic reviewApplied psychologyComputer scienceMedicineMEDLINEPedagogyPsychiatry

Abstract

fetched live from OpenAlex

An effective approach in early intervention for children and families, including child maltreatment prevention, is home-based services. Although several evidence-based programs exist, they are often grouped or delivered together, despite having different foci and approaches. This article describes the development and pilot phases of a trial evaluating the systematic braiding of 2 evidence-based home-based models, SafeCare and Parents as Teachers. We describe the methodology for braiding model implementation and curriculum, specifically focusing on how structured qualitative feedback from pilot families and providers was used to create the braided curriculum and implementation. Systematic braiding of 2 models at the implementation and curriculum levels is a mechanism that has the potential to meet the more comprehensive needs of families at risk for maltreatment.

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)0.036
metaresearch head score (Gemma)0.073
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: Methods · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.073
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.008
Research integrity0.0030.003
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 head0.641
GPT teacher head0.492
Teacher spread0.149 · 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
GenreMethods

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

Citations7
Published2016
Admission routes1
Has abstractyes

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