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Record W3071749381 · doi:10.1017/prp.2020.12

Addressing punitive violence against children in Australia, Japan and the Philippines

2020· article· en· W3071749381 on OpenAlexaff
Joan E. Durrant, Ashley Stewart-Tufescu, Christine A. Ateah, George W. Holden, Rashid Ahmed, Alysha Jones, Gia Ly, Dominique Pierre Plateau, Ikuko Mori

Bibliographic record

VenueJournal of Pacific Rim Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCorporal punishmentPunitive damagesPsychologyPunishment (psychology)Project commissioningDevelopmental psychologyChild disciplinePublishingSocial psychologySuicide preventionPoison controlPolitical scienceMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Physical and emotional punishment of children is highly prevalent in the Asia-Pacific region. These actions predict a range of physical and emotional harms, prompting a worldwide effort to eliminate them. A key strategy in this effort is to change parental beliefs regarding the acceptability of physical and emotional punishment. The Positive Discipline in Everyday Parenting (PDEP) program was designed to change those beliefs by teaching parents about child development and strengthening their problem-solving skills. A sample of 377 parents in the Asia-Pacific region completed the program: 329 mothers and 47 fathers of children ranging in age from infancy to adolescence. The parents lived in Australia ( n = 135), Japan ( n = 172) or the Philippines ( n = 70). In all three countries, parents’ approval of punishment in general, and physical punishment specifically, declined and they became less likely to attribute typical child behavior to intentional misbehavior. By the end of the program, at least 75% of parents in each country felt better prepared to respond nonviolently to conflict with their 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.091
GPT teacher head0.371
Teacher spread0.281 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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