Journal article
Simulation Detection in Handwritten Documents by Forensic Document Examiners
Journal of forensic sciences, v 60(4), pp 936-941
01 Jul 2015
PMID: 26190151
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This study documents the results of a controlled experiment designed to quantify the abilities of forensic document examiners (FDEs) and laypersons to detect simulations in handwritten documents. Nineteen professional FDEs and 26 laypersons (typical of a jury pool) were asked to inspect test packages that contained six (6) known handwritten documents written by the same person and two (2) questioned handwritten documents. Each questioned document was either written by the person who wrote the known documents, or written by a different person who tried to simulate the writing of the person who wrote the known document. The error rates of the FDEs were smaller than those of the laypersons when detecting simulations in the questioned documents. Among other findings, the FDEs never labeled a questioned document that was written by the same person who wrote the known documents as "simulation." There was a significant statistical difference between the responses of the FDEs and layperson for documents without simulations.
Metrics
Details
- Title
- Simulation Detection in Handwritten Documents by Forensic Document Examiners
- Creators
- Moshe Kam - New Jersey Institute of TechnologyPramod Abichandani - Drexel UniversityTom Hewett - Drexel Univ, Dept Psychol, Philadelphia, PA 19104 USA
- Publication Details
- Journal of forensic sciences, v 60(4), pp 936-941
- Publisher
- Wiley
- Number of pages
- 6
- Grant note
- T-2843; W91CRB -08-C0008 / Technical Support Working Group (TSWG) TASK
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology); Computer Science
- Web of Science ID
- WOS:000359262900013
- Scopus ID
- 2-s2.0-84938196813
- Other Identifier
- 991019312451604721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Medicine, Legal