1,721,407 research outputs found
The likelihood approach to compare populations : a study on DNA evidence and pitfalls of intuitions
No full textThe paper follows on from earlier work [Taroni F and Aitken CGG. Probabilistic reasoning in the law, Part 1: assessment of probabilities and explanation of the value of DNA evidence. Science & Justice 1998; 38: 165-177]. Different explanations of the value of DNA evidence were presented to students from two schools of forensic science and to members of fifteen laboratories all around the world. The responses were divided into two groups; those which came from a school or laboratory identified as Bayesian and those which came from a school or laboratory identified as non-Bayesian. The paper analyses these responses using a likelihood approach. This approach is more consistent with a Bayesian analysis than one based on a frequentist approach, as was reported by Taroni F and Aitken CGG. [Probabilistic reasoning in the law, Part 1: assessment of probabilities and explanation of the value of DNA evidence] in Science & Justice 1998
Media and Health
No full textNews media are the principal conduit of information about medicine and shape the attitudes of public opinion, physicians, researchers, and policy-makers. However, researchers and policy advocates deem media health with opposing attitudes: they are faulted as courting sensationalism and raising expectations but are also used for promoting behavioral changes from adopting healthier lifestyles to choosing health insurance plans. In fact, different media have different effects in communicating different issues to different audiences. This requires examining production, content, and audience reception of media messages in a common circuit of communication, starting from medical journals and scientists' press releases which are the principal sources of information for journalists writing about medicine. The article describes three broad models of health communication; engages with an internalist and an externalist view of the cozy relations at the interfaces between media and medicine and examines its reception by active audiences
Probabilistic evidential assessment of gunshot residue particle evidence (Part I): Likelihood ratio calculation and case pre-assessment using Bayesian networks
No full textWell developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in\ud
gunshot residue (GSR) particles, such analyses provide no information about a given particle’s actual source. Possible origins for which scientists may need to account for are a primary exposure to the\ud
discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction\ud
and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists inmaking the issue tractable within a probabilistic perspective. The proposed models\ud
focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment
Il significato delle evidenze: l'importanza dello scienziato forense nella prevenzione dell'errore
No full textIl ruolo della scienza forense è quello di garantire la qualità scientifica dell’elemento di prova trasmesso e discusso in sede dibattimentale, e che – sempre più sovente – rappresenta il perno fondamentale sul quale si basa un verdetto di condanna.
In riferimento alla prova detta scientifica, cioè all’utilizzo in sede dibattimentale di elementi di prova come il DNA, le impronte digitali o le micro-tracce (frammenti di vetro o di pitture, fibre tessili, residui di polvere da sparo, ecc.), è ormai accertato che errori d’analisi e di valutazione abbiano dato origine ad errori giudiziari. Ne sono la prova i casi analizzati dalla fondazione Innocent Project e pubblicati in alcuni articoli scientifici. Non è così infrequente che vengano commessi errori da parte degli operatori di polizia scientifica durante la fase di ricerca delle tracce sui luoghi di un crimine, di raccolta e di trasporto delle stesse o durante la raccolta di elementi comparativi provenienti dai luoghi, da persone sospettate o dalle vittime. Anche durante la fase di analisi nei laboratori specializzati dei reperti raccolti possono verificarsi errori. Contaminazioni sia sui luoghi dell’intervento o in fase di analisi possono caratterizzare in modo errato i reperti. Le analisi possono infatti mettere
in evidenza false associazioni tra le caratteristiche analizzate sui reperti e quelle degli elementi di comparazione (per esempio il profilo genetico di un sospetto) e contribuire
all’incriminazione di un sospetto erroneamente ritenuto all’origine di un dato reperto. Questi aspetti hanno indotto in errore varie Corti di giustizia.
Secondo i dati pubblicati dalla fondazione Innocent Project americana, e inerenti
prevalentemente a casi da loro analizzati dove la prova genetica del DNA ha svolto un ruolo fondamentale nel giudizio, una parte cospicua degli errori giudiziari individuati, sono stati alimentati da criticità connesse ai risultati delle analisi sui reperti scientifici. Il problema non si limita alla sola gestione della prova genetica; sono stati ugualmente riconosciuti casi di errori giudiziari alimentati da un apporto informativo fuorviante connesso ad altri tipi di tracce.
Oltre alla negligenza colpevole da parte di scienziati forensi, che può portare a perseguire e successivamente condannare persone innocenti per crimini che non hanno commesso, vi sono lacune di base caratterizzanti l’uso delle scienze forensi che possono talvolta spingere gli investigatori in direzioni sbagliate o i giudici a verdetti ingiustificati da un punto di vista scientifico. Questo capitolo presenterà alcuni esempi e cercherà di sottolineare come lo scienziato forense debba garantire la necessaria qualità al suo operato.
Sembra dunque superfluo ricordare come il ruolo svolto dagli esperti che operano sui luoghi e nei laboratori sia di primaria importanza per garantire credibilità al risultato scientifico. Questo aspetto, seppur fondamentale, non è sufficiente a scongiurare errori giudiziari. È imperativo saper inquadrare logicamente le conclusioni peritali, ed è su questo punto che si focalizzerà questo capitolo.
Partendo dal diffuso ricorso alla prova del DNA nella pratica legale e dal generale
riconoscimento di un’aura d’infallibilità che spesso lo contraddistingue, sarà possibile illustrare questo aspetto facendo luce su alcuni errori commessi quotidianamente nella gestione di questo elemento di prova
Decision theoretic properties of forensic identification: underlying logic and argumentative implications.
No full textThe field of forensic science has profited from recent advances in the elicitation of various kinds probabilistic data. These provide the basis
for implementing probabilistic inference procedures (e.g., in terms of likelihood ratios) that address the task of discriminating among
competing target propositions. There is ongoing discussion, however, whether forensic identification, that is, a conclusion that associates a
potential source (such as an individual or object) with a given item of scientific evidence (e.g., a biological stain or a tool mark), can, if ever,
be based on purely probabilistic argument. With regard to this issue, the present paper proposes to analyze the process of forensic
identification from a decision theoretic point of view. Existing probabilistic inference procedures are used therein as an integral part. The idea underlying the proposed analyses is that inference and decision are connected in the sense that the former is the point of departure for the latter. As such the approach forms a coordinated whole, that is a framework also known in the context as ‘full Bayesian (decision) approach’. This study points out that, as a logical extension to purely probabilistic reasoning, a decision theoretic conceptualization of forensic identification allows the content and structure of arguments to be examined from a reasonably distinct perspective and common fallacious interpretations to be avoided
The decisionalization of individualization
Full text linkThroughout forensic science and adjacent branches, academic researchers and practitioners continue to diverge in their perception and understanding of the notion of ‘individualization’, that is the claim to reduce a pool of potential donors of a forensic trace to a single source. In particular, recent shifts to refer to the practice of individualization as a decision have been revealed as being a mere change of label [1], leaving fundamental changes in thought and understanding still pending. What is more, professional associations and practitioners shy away from embracing the notion of decision in terms of the formal theory of decision in which individualization may be framed, mainly because of difficulties to deal with the measurement of desirability or undesirability of the consequences of decisions (e.g., using utility functions). Building on existing research in the area, this paper presents and discusses fundamental concepts of utilities and losses with particular reference to their application to forensic individualization. The paper emphasizes that a proper appreciation of decision tools not only reduces the number of individual assignments that the application of decision theory requires, but also shows how such assignments can be meaningfully related to constituting features of the real-world decision problem to which the theory is applied. It is argued that the decisonalization of individualization requires such fundamental insight to initiate changes in the fields’ underlying understandings, not merely in their label
Forensic inference and statistics for the evaluation and interpretation of evidence
No full textEvidence in a criminal investigation and trial should be evaluated and interpreted in the best manner possible. An excellent, and widely supported, approach to evaluation is one - by nature probabilistic - based on the likelihood ratio, the ratio of the probability of the evidence if a certain (set of) proposition(s) (e.g., prosecution) is assumed true to the probability of the evidence if a contrasting (set of) proposition(s) (e.g., defence) is assumed true. The justification for this approach is given together with a note of the benefits arising from the use of this ratio. There is a discussion about the meaning of probability as a measure of belief, the use of numerical assignments and verbal expressions and the use of the likelihood ratio for interpretation. It is explained how beliefs can be updated in the light of new evidence, how multiple pieces of evidence may be evaluated with the use of graphical structures and how uncertainty associated with the numerical evaluation, which is probabilistic, may be handled. A procedure for judgement of the quality of the mathematical formulae used in the calculation of the likelihood ratio is outlined. A conclusion gives three important principles that an expert, and a forensic scientist in particular, should follow when trying to understand the importance of evidence
A probabilistic graphical model for assessing equivocal evidence
Full text linkThe Bayes’ theorem can be generalized to account for uncertainty on reported evidence. This has an impact on the value of the evidence, making the computation of the Bayes factor more demanding, as discussed by Taroni, Garbolino, and Bozza (2020). Probabilistic graphical models can however represent a suitable tool to assist the scientist in their evaluative task. A Bayesian network is proposed to deal with equivocal evidence and its use is illustrated through examples
Statistics and the evaluation of evidence for forensic scientists
No full textThe third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That’s why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It’s written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence.
Discusses the entire chain of reasoning–from evidence pre-assessment to court presentation;
Includes material for the understanding of evidence interpretation for single and multiple trace evidence;
Provides real examples and data for improved understanding.
Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework
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