首页 | 本学科首页   官方微博 | 高级检索  
     


Metric forensic anthropology decisions: Reliability and biasability of sectioning-point-based sex estimates
Authors:Stephanie Hartley  Allysha Powanda Winburn  Itiel E. Dror
Affiliation:Department of Anthropology, University of West Florida, Pensacola, Florida, USASearch for more papers by this authorItiel E. Dror PhD,
First published: 02 November 2021
Citations: 1
Presented at the 73rd Annual Scientific Meeting of the American Academy of Forensic Sciences, February 15–19, 2021, held virtually.
Abstract:Subjective decisions make human cognitive processes more susceptible to bias and error. Specifically, research indicates that additional context biases forensic anthropologists’ morphological analyses. To address whether metric analyses are also subject to bias, we conducted a pilot study in which 52 experienced osteologists measured a difficult-to-classify human femur, with or without additional contextual information. Using a metric sectioning-point sex-estimation method, participants provided a sex estimate for individual skeletal element(s) and, when given multiple elements, the combined skeletal assemblage. Control group participants (n = 24) measured only the femur. In addition to the femur, bias group participants (n = 28) either measured a female humerus and viewed a female-biasing photograph (n = 14) or measured a male humerus and viewed a male-biasing photograph (n = 14). We explored whether the experts in the different groups would differ in: (1) femoral measurements; (2) femoral sex-estimation conclusions; and (3) final sex-estimation conclusions for the skeletal assemblage. Although the femoral measurements and femoral sex estimates were comparable across groups, the overall sex estimates in the female-biased group were impacted by contextual information—differing from both the control and male-biased groups (p < 0.001). Our results demonstrate that cognitive bias can occur even in metric sex-estimation conclusions. Specifically, this occurred when the metric data and single-element sex estimates were synthesized into an overall estimate. Thus, our results suggest that metric methods are most vulnerable to bias when data are synthesized into an overall conclusion, highlighting the need for bias countermeasures and comprehensive statistical frameworks for synthesizing metric data to mitigate the effects of cognitive bias.
Keywords:bias countermeasures  biasing context  cognitive bias  confirmation bias  error  expert decision making  forensic anthropology  standardization
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号