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Record W2127094802 · doi:10.1002/acp.3001

Safeguarding Youth Interrogation Rights: The Effect of Grade Level and Reading Complexity of Youth Waiver Forms on the Comprehension of Legal Rights

2014· article· en· W2127094802 on OpenAlexaffabout
Stuart Freedman, Joseph Eastwood, Brent Snook, Kirk Luther

Bibliographic record

VenueApplied Cognitive Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMemorial University of NewfoundlandOntario Tech UniversityBishop's University
Fundersnot available
KeywordsWaiverInterrogationSafeguardingPsychologyComprehensionReading (process)LawReading comprehensionSocial psychologyPolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

Summary The extent to which youths understand their interrogation rights was examined. High school students (N = 160) from five different grades were presented with one of two Canadian youth waiver forms—varying widely in reading complexity—and tested on their knowledge of their legal rights. Results showed that comprehension of both waiver forms was equally deficient, and systematic misunderstandings of vital legal rights were discovered (e.g., the right to remain silent). There was also a positive linear relationship between high school grade level and amount of comprehension. Potential ways to enhance youths' understanding of their rights and provide them protection during interrogations are discussed. Copyright © 2014 John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.026
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 score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.331
Teacher spread0.257 · 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

Citations24
Published2014
Admission routes2
Has abstractyes

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