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Record W4200195181 · doi:10.29173/wclawr52

“But I Wasn’t There!”

2021· article· en· W4200195181 on OpenAlexvenueno aff
Wendy P. Heath, Joshua Stein, Sabreen P. Afiouni

Bibliographic record

VenueThe Wrongful Conviction Law Review · 2021
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsnot available
FundersUniversity of Oxford
KeywordsAlibiConvictionPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Using the exoneree summaries in the Innocence Project and the documentation in the Innocence Record, we analyze the content of the alibis of those who have been wrongly convicted and exonerated with the use of DNA. Sixty-five percent of the 377 DNA exonerees had an alibi. Fifty-one percent reported that their alibi corroborators were friends and/or family members, while only about 10% presented physical evidence to support their alibi. Those with an alibi were significantly less likely to falsely confess than those without an alibi. Eyewitnesses were significantly more likely to be a contributing cause of conviction for those with an alibi than for those without an alibi, and 27% of the exonerees with an alibi had only eyewitness evidence to implicate them. Those that had an alibi were also more likely to claim that they had an inadequate defense than those that did not have an alibi. We conclude this paper with recommendations for reforms and future research.

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)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.042
GPT teacher head0.346
Teacher spread0.304 · 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 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

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