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Record W3044181713 · doi:10.1111/1468-2230.12565

Fingerprint Comparison and Adversarialism: The Scientific and Historical Evidence

2020· article· en· W3044181713 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

VenueModern Law Review · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsFingerprint (computing)Scientific evidenceCategorical variableMainstreamAdversarial systemPsychologyIdentity (music)LegislationLawEpistemologyPolitical scienceComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Abstract This article suggests that lawyers and courts are largely oblivious to scientific insights regarding the value and limitations of latent fingerprint evidence. It proceeds through a detailed historical analysis of the way fingerprint evidence has been reported and challenged. It compares legal responses with mainstream scientific research. Our analysis shows that fingerprint evidence is routinely equated with categorical proof of identity notwithstanding scientific warnings that such an approach is ‘indefensible’. We find that legal challenges to latent fingerprint evidence have been uniformly focused on adjectival issues (e.g. compliance with enabling legislation), leaving the validity and accuracy of this subjective comparison technique virtually unexamined since its first reception at the very beginning of the twentieth century. Lack of legal engagement with validity, error and scientific research suggest that adversarial procedures have not worked effectively to secure scientifically reliable expert evidence and that legal personnel struggle with elementary scientific reasoning.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.900
Threshold uncertainty score0.211

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)0.0000.000

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 head0.110
GPT teacher head0.332
Teacher spread0.222 · 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