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Record W2259003359 · doi:10.7870/cjcmh-2014-018

Preventing Punitive Violence: Preliminary Data on the Positive Discipline in Everyday Parenting (PDEP) Program

2014· article· en· W2259003359 on OpenAlexaffvenueabout
Joan E. Durrant, Dominique Pierre Plateau, Christine A. Ateah, Ashley Stewart-Tufescu, Alysha Jones, Gia Ly, Leslie Barker, George W. Holden, Colleen Kearley, Janice MacAulay, Ray DeV. Peters, Sombat Tapanya

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2014
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsQueen's UniversityAlberta Health ServicesUniversity of Manitoba
Fundersnot available
KeywordsPunitive damagesPunishment (psychology)Corporal punishmentPsychologyAngerChild disciplineDevelopmental psychologySocial psychologyPoison controlHuman factors and ergonomicsMedicinePolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Most physical violence against children is punitive in intent. The United Nations has called for the elimination of physical punishment of children and for the development of programs teaching nonviolent resolution of parent-child conflict. A focused effort is required to shift entrenched, intergenerationally transmitted, and culturally normalized belief systems about physical punishment. Positive Discipline in Everyday Parenting (PDEP) was developed to meet this need. Its short-term objectives are to: 1) reduce approval of physical punishment; 2) normalize parent-child conflict; and 3) strengthen parenting self-efficacy. PDEP was delivered by trained program facilitators to 321 parents living in 14 cities in Canada. Responses to pre and posttest questionnaires suggest that parents who completed postprogram measures were less likely to both approve of physical punishment and view typical parent-child conflict as misbehaviour on the part of the child, and also to have greater parenting self-efficacy. More than 90% believed more strongly that parents should not use physical punishment, and that PDEP would help them control their anger and build stronger relationships with their children. PDEP is a promising approach to the prevention of punitive violence against children.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.074
GPT teacher head0.383
Teacher spread0.308 · 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.

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

Citations44
Published2014
Admission routes3
Has abstractyes

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