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Record W2968929103 · doi:10.1002/acp.3598

The power of technology: Examining the effects of digital visual evidence on jurors' processing of trial information

2019· article· en· W2968929103 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Cognitive Psychology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicArtificial Intelligence in Law
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComprehensionPsychologyVerdictPresentation (obstetrics)Modality (human–computer interaction)Evidence-based practiceDigital evidenceSocial psychologyCognitive psychologyLinguisticsDigital forensicsLawComputer science

Abstract

fetched live from OpenAlex

Summary With the emergence of “electronic courtrooms” in North America, lawyers are increasingly using PowerPoint® to assist with their presentation of case evidence. The current study examined whether evidence complexity and presentation modality influenced participants' comprehension of case evidence and verdict decisions. Participants read a trial transcript from a criminal case that contained DNA evidence, which varied by complexity (simple or complex) and presentation modality (written or PowerPoint®). Participants completed comprehension questions to assess their understanding of the case evidence and rendered a verdict. Results demonstrated that neither the complexity nor the modality of the presented evidence influenced participants' comprehension of the evidence; however, participants who viewed evidence within a PowerPoint® were significantly more likely to render guilty verdicts than those who viewed written evidence. We discuss the theoretical and practical implications of these findings and propose suggestions for future research on the use of digital technology in the courtroom.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.038
GPT teacher head0.394
Teacher spread0.356 · 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