物证鉴定范式发展（一）：传统明确结论范式
王桂强
物证鉴定范式发展（一）：传统明确结论范式
Forensic Paradigm Development. Part 1: The Traditional Paradigm of Categorical Conclusions
物证鉴定范式是解释物证结果证据意义并形成鉴定意见过程中采用的科学理论和方法。物证鉴定领域正在经历从传统的物证来源明确结论范式向物证结果似然比评估范式转换。传统物证鉴定范式以特征唯一性作为科学基础假设，已有100余年发展和应用历史，应用于除DNA物证以外的几乎所有物证。鉴定人通过检测和比对物证和样本特征确定二者特征是否匹配，并采用阈值决策方式给出物证和样本来源相同或来源不同意见。基于物证明确来源意见和案件其他证据信息，决策者再做出相关的行为事实推论，作为被告犯罪与否的中间证据事实。在传统范式中，鉴定人从物证和样本特征结果得到物证明确来源意见的过程是一个演绎推理过程：大前提是物证特征唯一性假设，小前提是特征匹配（或不匹配）结果，结论是物证和样本来源相同（或不同）。只要大前提和小前提为真，传统范式的来源明确意见就正确。然而，随着DNA物证结果概率评估方法的发展和成熟，一些学者质疑特征唯一性假设缺少实证证明，进而认为失去这一前提的传统范式的演绎推理无效，因此传统物证来源明确意见范式被认为缺少坚固的科学基础。
The forensic paradigm is the scientific theories and methods used in the process of interpreting the findings of forensic examination and forming expert opinion. There is a paradigm shift from the traditional paradigm of categorical source conclusions to the paradigm of evaluative opinion. The traditional forensic paradigm is based on the assumption of feature uniqueness. The traditional paradigm of forensic science has a history of over 100 years of development and application, and has been applied to almost all physical evidence except DNA evidence. After detecting and comparing trace evidence from crime scene and known source sample, examiner will determine whether the features of the trace evidence match features of the sample, and will use threshold decision-making to give opinions on the trace evidence and the sample came from a same source or from different sources. In the traditional paradigm, the process by which examiner forms a categorical source opinions from results of the features is a deductive reasoning process: the major premise is the assumption of the uniqueness of trace features, the minor premise is the results of feature matching (or no-match), and the conclusion is that the trace and sample has same (or different) source. As long as the major and minor premises are true, the categorical opinion on source of the traditional paradigm is correct. However, with the development and maturity of evaluative methods for forensic DNA results, some scholars questioned the lack of empirical proof for the hypothesis of feature uniqueness in the traditional forensic paradigm, and thus believe that deductive reasoning without a major premise of the assumption of the trace features uniqueness has no validity, and therefore, the categorical source opinion in the traditional paradigm lacks a solid scientific foundation.
物证鉴定 / 特征匹配 / 阈值决策 / 明确结论 / 传统范式 {{custom_keyword}} /
forensic science / feature matching / threshold decision-making / categorical conclusions / traditional paradigm {{custom_keyword}} /
| [1] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [2] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [3] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [4] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [5] |
黎智辉, 谢兰迟, 王桂强, 等. 基于人脸特征相似度分数似然比的人脸比对方法[J]. 刑事技术, 2019, 44(1): 1-8.
在法庭科学中,特征比对是进行物证检验的核心方法之一,应用于几乎所有专业。基于统计框架的特征比对客观方法,是当前法庭科学发展的方向。本文就影像专业的人脸特征比对方法展开研究。通过深入分析当前基于深度学习的人脸特征进行比对的特点,开展了大规模数据的特征比对实验,统计了深度学习特征比对分数的分布,结合贝叶斯统计框架下基于分数似然比的模型,提出基于深度学习特征相似度分数似然比的人脸比对方法。我们的实验结果和分析,支撑了人脸特征比对客观方法的实际应用,也丰富了基于统计的法庭科学特征比对方法。
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Feature-comparison is one of the core methods among forensic evidence test, almost being applied by every professional subject. The feature-comparison method, based on the statistical framework, is objective, thus becoming the on-going direction of forensic science. Facial feature comparison is explored in this paper. Through in-depth characteristic analysis of the current deep learning with face features, the facial feature comparison is carried out into relevant large-scale data, thereby having obtained the statistical distributions of facial feature comparison score by deep-learning. Accordingly, the facial comparison approach is proposed at the basis of features' deep-learning coupled into the model of score-based likelihood ratio under Bayesian framework. The experimental results are supportive for the facial feature comparison to apply, demonstrating one more enrichment of the methods about forensic feature comparison based on statistics.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [6] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [7] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [8] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [9] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [10] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [11] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [12] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [13] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [14] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [15] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [16] |
U.S. Department of Justice. Fingerprint sourcebook[M/OL]. Washington DC, USA: National Institute of Justice, 2011 [2023-11-03]. http://www.nij.gov/pubs-sum/225320.htm.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [17] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [18] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [19] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [20] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [21] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [22] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [23] |
National Research Council. Forensic analysis: weighing bullet lead evidence[M]. Washington DC: National Academy Press, 2004.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [24] |
National Research Council. Strengthening forensic science in the United States: a path forward[R/OL]. Washington, DC: The National Academies Press, 2009 [2023-11-03]. https://doi.org/10.17226/12589.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [25] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [26] |
PCAST. Report on forensic science in criminal courts: ensuring scientific validity of feature-comparison methods[R]. President’s Council of Advisors on Science and Technology, 2016.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [27] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [28] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [29] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [30] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [31] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [32] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [33] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [34] |
The 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.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [35] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [36] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [37] |
The forensic sciences are under review more so than ever before. Such review is necessary and healthy and should be a continuous process. It identifies areas for improvement in quality practices and services. The issues surrounding error, i.e., measurement error, human error, contextual bias, and confirmatory bias, and interpretation are discussed. Infrastructure is already in place to support reliability. However, more definition and clarity of terms and interpretation would facilitate communication and understanding. Material improvement across the disciplines should be sought through national programs in education and training, focused on science, the scientific method, statistics, and ethics. To provide direction for advancing the forensic sciences a list of recommendations ranging from further documentation to new research and validation to education and to accreditation is provided for consideration. The list is a starting point for discussion that could foster further thought and input in developing an overarching strategic plan for enhancing the forensic sciences.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [38] |
Recent challenges have brought the discipline of firearms and tool mark identification to the forefront in recent court cases. This article reviews those challenges and offers substantial support for the scientific foundations of the firearms and tool mark identification discipline. A careful review of the available literature has revealed that firearms and tool mark identification is rooted in firm scientific foundations, critically studied according to the precepts of the scientific method culminating in the Association of Firearms and Toolmark Examiners' Theory of Identification. Firearms and tool mark identification has been validated in a manner appropriate for evidence of the kind to be expected in firearms and tool mark examinations. Proficiency tests and error rates have been studied and can provide consumers of the disciple with a useful guide as to the frequency with which misidentifications are reported in the community using appropriate methodologies and controls. As a result, the primary issues in recent challenges do not invalidate the firearms and tool mark discipline as a science nor should it detract it from its admissibility in a court of law.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [39] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [40] |
SWGFAST. Standards for examining friction ridge impressions and resulting conclusions draft for comment[R]. Scientific Working Group on Friction Ridge Analysis Study and Technology, Version 2.0, 2013.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [41] |
Department of the Army Defense Forensic Science Center. Information paper, subject: use of the term “identification” in latent print technical reports[R]. 2015.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [42] |
Department of the Army Defense Forensic Science Center. Information paper, subject: modification of latent print technical reports to include statistical calculations[R]. 2017.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [43] |
FRSOSAC. Standard for examining friction ridge impressions[R]. Friction Ridge Subcommittee Organization for Scientific Area Committees (OSAC) for Forensic Science, Version 1.0, 2020.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [44] |
王桂强. 物证鉴定的技术方法确认和标准操作规程[J]. 刑事技术, 2006, 31(6): 3-8.
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{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [45] |
The extent to which cognitive biases may influence decision-making in forensic science is an important question with implications for training and practice. We conducted a systematic review of the literature on cognitive biases in forensic science disciplines. The initial literature search including electronic searching of three databases (two social science, one science) and manual review of reference lists in identified articles. An initial screening of title and abstract by two independent reviewers followed by full text review resulted in the identification of 29 primary source (research) studies. A critical methodological deficiency, serious enough to make the study too problematic to provide useful evidence, was identified in two of the studies. Most (n = 22) conducted analyses limited to practitioners (n = 17), forensic science trainees (n = 2), or both forensic science practitioners and students (n = 3); other analyses were based on university student or general population participants. Latent fingerprint analysis was examined in 11 studies, with 1-3 other studies found in 13 other disciplines or domains. This set of studies provides a robust database, with evidence of the influence of confirmation bias on analysts conclusions, specifically among the studies with practitioners or trainees presented with case-specific information about the "suspect" or crime scenario (in 9 of 11 studies examining this question), procedures regarding use of exemplar(s) (in 4 of 4 studies), or knowledge of a previous decision (in 4 of 4 studies). The available research supports the idea of susceptibility of forensic science practitioners to various types of confirmation bias and of the potential value of procedures designed to reduce access to unnecessary information and control the order of providing relevant information, use of multiple comparison samples rather than a single suspect exemplar, and replication of results by analysts blinded to previous results.Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [46] |
In recent years, a number of studies have demonstrated that forensic examiners can be biased by task-irrelevant contextual information. However, concerns relating to methodological flaws and ecological validity attenuate how much the current body of knowledge can be applied to real-life operational settings. The current review takes a narrative approach to synthesizing the literature across forensic science. Further, the review considers three main issues: (i) primary research on contextual bias within forensic science; (ii) methodological criticisms of this research; (iii) an alternative perspective that task-irrelevant contextual information does not always lead to error. One suggestion for future research is outlined, which is that studies on contextual bias in forensic decisions should be conducted in collaboration between forensic scientists and cognitive psychologists. Only then can rigorous and ecological valid experiments be created that will be able to assess how task-irrelevant contextual information influences forensic analysis and judgments in operationally valid settings.© 2019 American Academy of Forensic Sciences.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [47] |
王桂强. 物证鉴定错误问题研析[J]. 刑事技术, 2017, 42(6): 431-440.
物证鉴定错误是物证鉴定结果、结论或意见所表达和反映的事实情况本质上偏离了真实的事实情况,其包括物证鉴定结论错误和结论传递、理解及应用错误。依照错误来源,物证鉴定错误可以分为仪器错误、方法错误、认知偏见错误和人为错误四种类型。依照错误性质,物证鉴定错误可以分为物证来源鉴定结论的假阳性和假阴性错误、物证成分检验结论的定性和定量错误和物证推断检验结果错误。物证鉴定错误发生阶段,涉及物证发现、提取、包装、保存、特征检验、特征解释评估、结论报告和传递、结论理解和应用全过程。虽然现有的物证鉴定准确性和有效性的实证研究资料还无法给出能够反映实际案件物证鉴定情况并被广泛认同的一般错误率值,但这些资料已经表明包括指印、DNA、枪弹、咬痕、笔迹和毛发等常见物证的鉴定结论确实存在一定错误风险,并且这些实证研究资料可以帮助总结研究物证鉴定错误的出现规律和发现物证鉴定体系的薄弱点。
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Forensic error refers that the forensic conclusion itself and/or its reflecting arguments diverge from the reality. Forensic error consists of the errors amid the conclusions, those from producing, delivering, understanding and/or applying the conclusions since it can result from such various sources as instrument, method, bias and the artificial. According to the attribute, forensic error can also be of: 1) the false positive/negative conclusion in relation to source determination; 2) the unfaithful quantitative/qualitative assay in chemical detection; and 3) incorrect predicting opinions in evidence interpretation. Forensic error can occur in any one of all the stages of criminal justice from evidence-detecting/collecting in crime scene, evidence-packaging/preserving in transition, evidence-analyzing/interpreting in laboratory, report-writing and testimony-giving in conclusion-making until the conclusion-presenting/understanding in court. There are a lot of literatures that have been published in peer-reviewed journals about the empirical researches on validation and accuracy of forensic evidence. Although it is not possible to obtain a generally-accepted error rate reflecting real forensic casework by the empirical researches from the literatures, yet the acquired data do demonstrate that a risk of error really exists during forensic casework with the instances in identification of fingerprint, DNA, firearm, bite mark, handwriting and human hair, therefore capable of helping us understand the way and frequency of error occurrence so as to determine the weak spots and high-risk areas in forensic identification system.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
| [48] |
王桂强. 物证鉴定错误减少对策研究[J]. 刑事技术, 2018, 43(1): 1-10.
物证鉴定若存在错误风险则会危害严重。恰当的物证鉴定错误管理可以有效减少物证鉴定错误的发生,有助于及时发现物证鉴定错误并将损害减至最小。本文探讨了在物证鉴定全部过程中有效管理物证鉴定错误的十二条措施：1）以有组织方式有条理的开展物证发现、提取、标记、记录、包装、保存和送检工作;2）持续强化物证鉴定科学基础研究和方法确认;3）在物证鉴定检验过程中实施多人平行鉴定、技术评审和管理审核程序;4）建立透明的鉴定意见冲突解决和鉴定结论表述机制;5）采用适当程序和方法有效管理和控制物证鉴定认知偏见信息;6）实施物证鉴定结论例行核查机制;7）建立检验留样和全面记录机制;8）有效评估物证鉴定结论错误风险;9）建立有效的用户培训和交流机制;10）及时发现和整改物证鉴定错误;11）构建物证鉴定科学文化;12）加强物证鉴定人培训。
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Forensic error, when existing and even causing risks, will do very likely a lot of harm to the criminal justice system. Suitable forensic error management can be effectively reducing the error generating, timely detecting the error, and even lowering the error-incurred damage to minimum. This article will inquire into the strategies to mitigate forensic error by implementing a dozen of relevant measures. 1) To systematically and orderly carry out evidence discovering, collecting, labeling, recording, packaging, preserving and submitting. 2) To continually strengthen the researches on forensic science basis and validation of methods used in forensic laboratory. 3) To adopt the procedures of paralleling multiple examiners, technical review and administrative evaluation. 4) To establish a transparent conflict-resolution policy for settling disagreements in technical decision from examiners. 5) To effectively manage and control the biasing information in forensic analysis. 6) To carry out the procedure of regularly checking cases files in order to search/avoid error. 7) To create and run a procedure of both retaining evidential samples and completely documenting the analytic process for renewing methods or peer review to assess the previous conclusion. 8) To evaluate the risk from forensic conclusion error. 9) To develop an effective mechanism for training and interchanging between forensic participators. 10) To timely detect/rectify forensic error. 11) To build up scientific culture among the forensic community. 12) To strengthen training and education of forensic examiners.
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| [49] |
{{custom_citation.content}}
{{custom_citation.annotation}}
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