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Record W2017994299 · doi:10.1080/10538710801916564

The Use of the NICHD Protocol to Enhance the Quantity of Details Obtained from Children with Low Verbal Abilities in Investigative Interviews: A Pilot Study

2008· article· en· W2017994299 on OpenAlexaff
Jacinthe Dion, Mireille Cyr

Bibliographic record

VenueJournal of Child Sexual Abuse · 2008
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversité de MontréalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsSexual abuseProtocol (science)PsychologyVerbal abuseClinical psychologyDevelopmental psychologyMedicinePoison controlSuicide preventionMedical emergencyAlternative medicine

Abstract

fetched live from OpenAlex

This study explored the impact of the NICHD protocol to enhance the quantity and content of details reported by children with low verbal abilities. Thirty-four children aged from 6 to 14 were interviewed following their experience of sexual abuse. Half the interviews were conducted using the NICHD protocol. Results indicate that NICHD interviews contained more open-ended prompts and more details overall. Open-ended invitations yielded significantly more detailed responses than did closed-ended questions for both children with low and average verbal abilities. Although children with low verbal abilities provided fewer details than children with average verbal abilities, the NICHD protocol helped them provide detailed responses containing the core elements of the sexual abuse.

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)0.211
metaresearch head score (Gemma)0.283
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2110.283
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.005
Scholarly communication0.0030.003
Open science0.0040.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.091
GPT teacher head0.318
Teacher spread0.227 · 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.

Study designNon-randomized trial
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

Citations33
Published2008
Admission routes1
Has abstractyes

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