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Record W2911944590 · doi:10.1037/lhb0000319

Does video recording inhibit crime suspects? Evidence from a fully randomized field experiment.

2019· article· en· W2911944590 on OpenAlexaff
Saul M. Kassin, Melissa B. Russano, Aria Amrom, Johanna Hellgren, Jeff Kukucka, Victoria Z. Lawson

Bibliographic record

VenueLaw and Human Behavior · 2019
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsPsycINFOPsychologyGeneral partnershipCoding (social sciences)Legal psychologySocial psychologyMEDLINELawPolitical science

Abstract

fetched live from OpenAlex

In partnership with a small city police department, we randomly informed or did not inform 122 crime suspects that their interrogations were being video-recorded. Coding of all sessions indicated that camera-informed suspects spoke as often and as much as did those who were not informed; they were as likely to waive Miranda at the outset and later; they were as likely to make admissions and confessions, not just denials; and they were perceived no differently by detectives on a range of dimensions. Looking at distal outcomes, we observed no differences in ultimate case dispositions. In terms of policy and practice, results did not support the hypothesis that recording-even when transparent, as required in 2-party consent states-inhibits suspects or alters case dispositions. At least for now, this conclusion is empirically limited to situations in which cameras are concealed and to interrogations that do not involve juveniles, homicides, or drug crimes, which we a priori excluded from our sample. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0470.001

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 head0.029
GPT teacher head0.343
Teacher spread0.314 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations13
Published2019
Admission routes1
Has abstractyes

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