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Vol.14 No.1

The Personality Assessment Inventory (PAI) Profiles of Crime Victims
; (California Lutheran University) ; pp.1-29 https://doi.org/10.53302/kjfp.2023.03.14.1.1
초록보기
Abstract

This study confirmed the utility of the Personality Assessment Inventory (PAI) in assessing crime victims’ psychopathological symptoms. The t-scores of 22 PAI scales (4 validity scales, 11 clinical scales, 5 treatment scales, and 2 interpersonal scales) of 258 victims and 1,442 non-victims were compared. The victim group was found to have significantly higher scores for all scales except dominance (DOM) (no difference) and treatment rejection (RXR) (significantly lower), with an especially larger effect size in anxiety (ANX), anxiety-related disorders (ARD), depression (DEP), and suicidal ideation (SUI). Regarding the validity scales, the likelihood of the t-score being at or above the manual-based cut-off was 10.25 times inconsistency (ICN), 1.17 times infrequency (INF), and +5.15 times negative impression (NIM) higher in the victim group than in the non-victim group. These results may compromise the validity of profiles of victims’ clinical scales. Nevertheless, the PAI was found to be an adequate instrument for measuring several of the PTSD-related features that a victim of crime may experience. The need for a new standard for interpreting validity scales that considers the unique characteristics of crime victims was then discussed.

Effects of intermediary and statement inconsistency of child witness during cross-examination on mock juror’s judgment of statement credibility
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Abstract

Recently, the Korean Constitutional Court ruled that the provisions allowing video-recorded statements of underage sexual abuse victims as evidence were unconstitutional. As child victims have to participate in the cross-examination, the role of intermediaries might be increased to aid child witnesses’ communication in court. Therefore, this study aims to examine how an intermediary’s intervention affects mock jurors’ perception of statement credibility. Based on Expectancy Violation Theory, we hypothesized that when a lawyer asks inappropriate questions to a child witness during cross-examination, if the child’s statement is inconsistent despite the intervention of an intermediary, mock jurors would perceive the child as less credible. In a 2(intermediary present vs. not present) x 2(statement consistent vs. inconsistent) between-subjects experiment, 186 adult participants read one of the four sexual abuse case scenarios and then judged the credibility of a child witness. As a result, the credibility was judged lower when the child’s statements were inconsistent than when they were consistent. The intervention of the intermediary did not affect the mock juror’s perception of the child’s anxiety level, and there was no expectancy violation effect by the intermediary. Based on these results, the problems of child witness cross-examination and the need for a better understanding of the intermediary’s role were discussed.

Accuracy of statement consistency analysis using Triple+ extractions of natural language processing
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Abstract

Demand for statement analysis is increasing as the credibility of the victim's statement becomes more important in the investigation and trial of sexual offence cases. The consistency of the victim's statement is one of the main criteria for judging the credibility of a victim. In the era of 4th industrial revolution natural language processing technology is rapidly growing to analyze conversation contents. This study tried to verify the accuracy of statement consistency analysis using Triple+ extractions, a natural language processing technology. Trained evaluators conducted a statement consistency analysis on 57 actual transcripts of victim statements and compared them with the results of statement inconsistency analysis using Triple+. The Triple+ for 18 pairs of inconsistent sentences from victim statements were extracted and classified into 7 types of statement inconsistency. The rules of determining statement inconsistency for each type were established. The results showed that Triple+ correctly identified statement discrepancies 77% on the average. For subtypes of inconsistency classification accuracy varied as 100% for the direction, timing, and action, 75% for content denial, 66.7% for place, and 50% accuracy of event sequence and passive/active type were found. 93.8% accuracy was achieved in the judgment of 32 randomly selected pairs of consistent sentences. The results of this study suggest a potential for automatic statement inconsistency discrimination using Triple+ as supplementary tool for human expert statement analysis. The limitations of the existing natural language processing technology required for artificial intelligence statement analysis and the direction of future research are discussed.

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