MétaCan
Menu
Back to cohort
Record W4401742625 · doi:10.1111/lcrp.12269

Urgent issues and prospects on investigative interviews with children and adolescents

2024· article· en· W4401742625 on OpenAlexaff
Victoria Talwar, Angela M. Crossman, Stephanie D. Block, Sonja P. Brubacher, Rachel E. Dianiska, Ana Karen Espinosa Becerra, Gail S. Goodman, Mary Lyn Huffman, Michael E. Lamb, Kamala London, David La Rooy, Thomas D. Lyon, Lindsay C. Malloy, Lauren E. Maltby, Van P. Nguyen Greco, Martine B. Powell, Jodi A. Quas, Corey J. Rood, Sydney D. Spyksma, Linda C. Steele, Zsófia A. Szojka, Yuerui Wu, Breanne E. Wylie

Bibliographic record

VenueLegal and Criminological Psychology · 2024
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsOntario Tech UniversityUniversity of OttawaMcGill University
Fundersnot available
KeywordsBest practicePsychologyPublic relationsEngineering ethicsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Abstract While there has been considerable research on investigative interviews with children over the last three decades, there remains much to learn. The aim of this paper was to identify some of the issues and prospects for future scientific study that most urgently need to be addressed. Across 10 commentaries, leading scholars and practitioners highlight areas where additional research is needed on investigative interview practices with youths. Overarching themes include the need for better understanding of rapport‐building and its impact, as well as greater focus on social‐cultural and developmental factors and the needs of adolescents. There are calls to examine how interviews are occurring in real‐world contexts to better inform best practice recommendations in the field, to find means for ensuring better adherence to best practices among various groups of practitioners, and to understand their importance and impact when not followed, including by those testifying in courts. All reflect the need to better address that recurring challenge of reliably and consistently eliciting accurate and credible information from potentially reluctant young witnesses.

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)0.000
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 score0.805
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.117
GPT teacher head0.359
Teacher spread0.242 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueLegal and Criminological PsychologySame topicMemory Processes and InfluencesFrench-language works237,207