形态特征在性别估计中的可靠性检验

A. Klales, H. Garvin, Timothy P. Gocha, Kate M Lesciotto, M. Walls
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引用次数: 2

摘要

形态学的头骨和耻骨特征通常用于法医人类学案件的性别估计,Walker(2008)和Klales等人(2012)的方法通常被采用。本研究旨在综合评估颅骨和外阴特征评分的可靠性,以及观察者评分差异对性别估计准确性的影响。从以往的研究结果进行总结,并编制成表进行比较。本研究的数据由Walker(2008)和Kales等人(2012)的特征评分(颅骨n = 392,公众n = 443)的大量汇编组成,这些特征评分由7位不同专业水平的研究人员贡献。在观察者内部和观察者之间对特征得分进行了分析,并评估了观察者之间正确性别分类的变化,特别强调了观察者经验的影响。统计结果表明,Walker(2008)和Klales et al.(2012)所使用的特征都可以可靠地得分,除了心理卓越性,这在研究和个体之间表现出相当大的差异。由此产生的性别估计随着经验水平的提高而提高,两种方法在专家中准确率最高。尽管新手观察者与经验丰富的观察者在性状得分上有很好的一致性,但微小的得分差异会对分类准确性产生负面影响,特别是在Klales等人(2012)的方法中,准确率下降了15%以上。研究结果强调了这些性别估计方法的经验、人类差异和训练的重要性,也表明来自专家从业者的数据可以合并到更大的数据库中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining the Reliability of Morphological Traits for Sex Estimation
Morphological skull and pubic traits are routinely used in forensic anthropological casework for sex estimation, with the Walker (2008) and Klales et al. (2012) methods commonly employed. This research aims to present a comprehensive evaluation of reliability in skull and pubic trait scoring and the implications of observer scoring variation on sex estimation accuracy. Results from previous studies are summarized and compiled into tables for comparisons. Data from this study are composed of a large compilation of Walker (2008) and Kales et al. (2012) trait scores (skull n = 392, pubic n = 443) contributed by seven researchers of varying levels of expertise. Intra- and interobserver analyses were performed on the trait scores, and variations in correct sex classifications were assessed among observers, with particular emphasis on the effects of observer experience. Statistical results indicate that the traits utilized in Walker (2008) and Klales et al. (2012) can be reliably scored except for the mental eminence, which has shown considerable variation among studies and individuals. Resultant sex estimations improved with experience level, with the highest accuracy rates for both methods among experts. Although novice observers had good agreement in trait scores with more experienced observers, minor scoring differences negatively impacted classification accuracy, particularly in the Klales et al. (2012) method with more than a 15% drop in accuracy. The results highlight the importance of experience and exposure to human variation and training in these sex estimation methods and also suggests data from expert practitioners can be combined into larger databases.
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