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Record W3025232079 · doi:10.1177/1077559520930825

Young Children’s Ability to Describe Intermediate Clothing Placement

2020· article· en· W3025232079 on OpenAlexaff
Breanne E. Wylie, Stacia N. Stolzenberg, Kelly McWilliams, Angela D. Evans, Thomas D. Lyon

Bibliographic record

VenueChild Maltreatment · 2020
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsBrock University
Fundersnot available
KeywordsClothingSexual abusePsychologyInterviewPoison controlDevelopmental psychologyHuman factors and ergonomicsSocial psychologyMedicineMedical emergencySociologyHistory

Abstract

fetched live from OpenAlex

Children’s ability to adequately describe clothing placement is essential to evaluating their allegations of sexual abuse. Intermediate clothing placement (partially removed clothing) may be difficult for young children to describe, requiring more detailed explanations to indicate the location of clothing (e.g., the clothes were pulled down to the knees). The current study investigated 172 3- to 6-year-olds’ descriptions of clothing placement when responding to commonly used questions ( yes/no, forced-choice, open-choice, where), as well as children’s on-off response tendencies when describing intermediate placement (i.e., labeling the clothing as fully on or off). Results revealed that where questions were superior in eliciting intermediate descriptions, even for the youngest children. Children sometimes exhibited tendencies to describe intermediate placements as “on” or “off,” which varied by question-type and clothing placement. The implications of the findings for interviewing young children about sexual abuse are discussed.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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