Of Earprints, Fingerprints, Scent Dogs, Cot Deaths and Cognitive Contamination: A Brief Look at the Present State of Play in the Forensic Arena
Notice bibliographique
Résumé
Over the last decades, the importance of technical and scientific evidence for the criminal justice system has been steadily increasing. Unfortunately, the weight of forensic evidence is not always easy for the trier of fact to assess, as appears from a brief discussion of some recent cases in which the weight of expert evidence was either grossly over- or understated. Also, in recent years, questions surrounding the value of forensic evidence have played a major role in the appeal and revision stages of a number of highly publicized criminal cases in several countries, including the UK and the Netherlands. Some of the present confusion is caused by the different ways in which conclusions are formulated by experts working within the traditional approach to forensic identification, as exemplified by (1) dactyloscopy and (2) the other traditional forensic identification disciplines like handwriting analysis, firearms analysis and fibre analysis, as opposed to those working within the modern scientific approach used in forensic DNA analysis. Though most clearly expressed in the way conclusions are formulated within the diverse fields, these differences essentially reflect the scientific paradigms underlying the various identification disciplines. The types of conclusions typically formulated by practitioners of the traditional identification disciplines are seen to be directly related to the two major principles underpinning traditional identification science, i.e. the uniqueness assumption and the individualization principle. The latter of these is shown to be particularly problematic, especially when carried to its extreme, as embodied in the positivity doctrine, which is almost universally embraced by the dactyloscopy profession and allows categorical identification only. Apart from issues arising out of the interpretation of otherwise valid expert evidence there is growing concern over the validity and reliability of the expert evidence submitted to courts. While in various countries including the USA, Canada and the Netherlands criteria have been introduced which may be used as a form of input or output control on expert evidence, in England and Wales expert evidence is much less likely to be subject to forms of admissibility or reliability testing. Finally, a number of measures are proposed which may go some way to address some of the present concerns over the evaluation of technical and scientific evidence.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».