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Record W2264043653 · doi:10.1177/1365712715591462

Aging witnesses

2015· article· en· W2264043653 on OpenAlexafffund
Helene Love

Bibliographic record

VenueThe International Journal of Evidence & Proof · 2015
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsUniversity of Toronto
FundersLaw Foundation of British Columbia
KeywordsWitnessScholarshipEconomic JusticePsychologyCriminologyPopulationOrder (exchange)LawSociologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

With the population aging, judges will increasingly be faced with elder witnesses in their courtrooms. Despite the importance of elder witness testimony to the investigation and prosecution of crimes, an age-based lens has yet to be cast on this issue in legal scholarship to date. However, in the field of psychology there are a number of studies that detail how old age impacts a witness’s ability to perceive, remember and communicate an event in court. This paper bridges this gap between legal and psychological scholarship by reviewing the psychological studies on elder witnesses and describing, in practical terms, the implications of these studies on the legal treatment of elder witness evidence. Going forward, it is only with increased awareness of these differences between older and younger witnesses that the justice system can begin to understand how it needs to change in order to respond to the unique needs of this growing segment of the population.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.311
GPT teacher head0.458
Teacher spread0.147 · 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.

Study designNot applicable
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

Citations5
Published2015
Admission routes2
Has abstractyes

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