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Using Speech To Differentiate Between Genuine And False Rape Allegations

Using Speech To Differentiate Between Genuine And False Rape Allegations. By Professor Ray Bull (and Laura Hunt). 2. . Rape is a heinous crime with serious emotional and physical consequences ( Thornhill & Palmer, 2000 ).

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Using Speech To Differentiate Between Genuine And False Rape Allegations

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  1. Using Speech To Differentiate Between Genuine And False Rape Allegations By Professor Ray Bull (and Laura Hunt)

  2. 2. Rape is a heinous crime with serious emotional and physical consequences (Thornhill & Palmer, 2000). Not only women but also men are victims of rape (Jamel, Bull, & Sheridan, 2008). According to government data in England and Wales the number of rapes recordedby the police in 2006/2007 was 13,780 (Jansson, Povey, & Kaiza, 2007). However, rape is one of the most under-reported crimes; for example the 2001 British Crime Survey (Walby & Allen, 2004) found that only 15% of rapes came to the attention of the police. In terms of reported rapes, Jordan (2004) noted that subjective judgments may well be made by the police about rape victims’ credibility, with a focus on appraisals of (alleged) victims’ characteristics and contributory culpability. (Also see Her Majesty’s Crown Prosecution Service Inspectorate [HMCPSI]/Her Majesty’s Inspectorate of Constabulary [HMIC], 2007.). See Sleath and Bull (2012) for research on ‘rape myths’ held by some police.

  3. 3. The definition of a ‘false allegation’ is vital to discussing this topic and plays an important role in determining the number of allegations that are classified as false. However, as yet no definitive definition has been agreed. Furthermore very few studies have systematically and reliably examined the actual rate of false allegations (Aitken, 1993). One of the first studies to directly compare the behaviours reported in genuine allegations with those reported in fabricated allegations was conducted by Rainbow (1996). His study, however, lacked ecological validity as the sample of ‘false’ allegations was ‘simulated’ by female participants recruited for the purpose. Despite its limitations his study did offer some interesting findings, including that that the ‘simulated’ accounts contained less “inquisitive language” (although this variable was not defined). A similar methodology to Rainbow’s was used by Norton and Grant (2006) who found that simulated false allegations contained more rape myths than did true allegations. In their unpublished paper Woodhamsand Grant (2004) looked specifically at alleged rapists’ speech in ‘genuine’ and ‘false’ allegations and found that more offender utterances were reported in ‘genuine’ cases than in ‘false’ cases.

  4. 4. Much of the prior research on this topic, although valuable, has suffered from methodological weakness such as poor definitions of what constitutes a ‘false’ allegation, small sample sizes, lack of ecological validity, and lack of statistical interpretation/sophistication from which to draw firm conclusions (McDowell, 1992; Maclean, 1979; Marshall & Alison, 2006; Rainbow, 1996; Theilade & Thomsen, 1986; Woodhams & Grant, 2004). The present study attempted to overcome many of these problems and to provide a methodologically sounder investigation.

  5. 5. Determining that an allegation is ‘genuine’ or ‘false’ is a problematic task; the risk of a genuine victim subsequently claiming that an allegation was false cannot be eliminated, nor can the possibility that a person has been convicted of a rape that actually did not occur. However, in the present study measures were put in place to minimise the risk of such occurrences. A case was classified as a ‘false’ allegation if (1) the victim had made a retraction statement in which she admitted the allegation was fabricated, or (2) the victim had been charged with ‘wasting police time’ or ‘perverting the course of justice’. An allegation was classified as ‘genuine’ if the relevant person had been convicted of the offence.

  6. 6. The current study compared a sample of 160 ‘genuine’ rape allegations with 80 ‘confirmed false’ allegations. This sample size is greater than in many of the previous studies. The data collected were obtained directly from victim statements (i.e. resulting from police interviews) kept within the case files of the relevant national agency (i.e. ‘SCAS’). ‘SCAS’ is a unit in England/Wales with a national remit to collect cases of stranger rape, murder, and abduction from all police forces. All information contained within the case papers is coded and entered onto the Violent Crime Linkage Analysis System (ViCLAS) (which stores information on 62 variables of relevance) by a team of highly trained staff who input the relevant information which is taken primarily from the victim statement to/interview with the police.

  7. 7. For each of the 240 cases data were collated regarding the 62 categorical variables (contained within the ViCLAS database) plus age. Initially frequencies of behaviours among the two sets of cases were compared and significant associations were identified by conducting chi square analysis on each categorical variable. Where a statistically significant effect was found, the odds ratio was then calculated to explore the differentiating effect of that behaviour.

  8. 8. The 44 (out of 62) statistically significant effects from the chi squares and odds ratios included: type of approach (for two variables); aspects of the ‘victim’ (for three variables); location (for two variables); sexual behaviour (for seven variables); violence/theft (for four variables); resistance (for three variables); ‘verbal’ (for seventeen variables – to be mentioned on the next slide); how the matter was reported to the police (for six variables). (The 18 variables for which no significant effects were found were: multiple offenders, vehicle involved, initial contact outdoors, burglary, abduction, blitz approach, items brought to scene, foreign object insertion, sound precautions, victim restrained, first telling police, and the following six verbal themes: abusive language, compliments, justifications, reference to underwear, victim sexual practices, cruelty.)

  9. 9. The discriminating verbal variables included: ingratiating speech by perpetrator; perpetrator requests participation of the victim; perpetrator expresses curiosity about the victim; perpetrator requests sex acts; perpetrator makes threats; perpetrator makes disclosures; perpetrator asks if victim is enjoying it; perpetrator apologises; perpetrator makes more than ten utterances.

  10. 10 (of 13). A predictive model? To limit the number variables that were fed into the logistic regression model, only those of the discriminating 44 that had a significant effect at the p < 0.001 level and those with an odds ratio of greater than 3 or less than 0.33 were input as predictive variables. This resulted in 26 predictor variables which were initially fed into the model. They were then removed in an iterative process, with the final model containing five predictor variables and a constant, as detailed in the table on the next slide.

  11. Overall the model correctly classified 220 (91.7%) cases correctly. The false positive rate (classifying a case as genuine when it should have been false) was 7.5% and the false negative rate (classifying a case as false when it should have been genuine) was 8.75%. (Logistic regression model - R2 = .68 (Hosmer & Lemeshow), .58 (Cox & Snell), .80 (Nagelkerke). Model 2 (1) = 207.07, p < .001. *p < .05. **p < .01. ***p < .001.)

  12. 12 (of 13). Able to predict? To test the model a further 12 cases were requested from SCAS, four of which were false and eight of which were genuine. Using the five predictor variables from the logistic regression model (i.e. ‘theft’, ‘victim reported to police’, ‘verbal resistance’, ‘verbal theme of safe departure’, less than ten offender utterances’) these 12 cases were classified as ‘genuine’ or ‘false’. This served as a test of how robust the findings from the main analyses were and served to validate the model/to establish how useful the model would be with other cases. Ten of these ‘new’ 12 cases were accurately classified, with an accuracy rate for ‘genuine’ cases of 75%, an accuracy rate for ‘false’ allegations of 100% (thus the false positive rate was zero, and the false negative rate 25%).

  13. 13 (of 13). Thus, in our study the alleged rapists were reported by ‘victims’ to speak significantly more in ‘genuine’ allegations than in ‘false’ allegations. This may be because false allegers do not in advance of making an allegation think about offender speech because their thinking/planning is preoccupied with sexual acts. Our findings, when added to the somewhat similar ones of Rainbow (1996) and of Woodhams and Grant (2004), strongly suggest that those taking statements/interviewing alleged (stranger) rape victims should do so in a way that allows ‘genuine’ victims to provide comprehensive information about the (alleged) offender’s speech/verbal content.

  14. References Aitken, M. M. (1993). False allegation: A concept in the context of rape. Journal of Psychosocial Nursing, 31, 15 – 20. Her Majesty’s Crown Prosecution Service Inspectorate/Her Majesty’s Inspectorate of Constabulary. (2007). Without consent: A report on the joint review of the investigation and prosecution of rape offences. London, UK: Home Office. Jamel, J., Bull, R., & Sheridan, L. (2008). An investigation of the specialist police service provided to male rape survivors. International Journal of Police Science and Management, 10, 486-508. Jansson, K., Povey, D. & Kaiza, P. (2007). Violent and sexual crime. In S. Nicholas, C. Kershaw & A. Walker (Eds.) Crime in England and Wales 2006 / 2007. London: Home Office.

  15. Jordan, J. (2004). Beyond belief? Police, rape and women’s credibility. Criminal Justice, 4, 29-59. Maclean, N. M. (1979). Rape and false accusations of rape. Police Surgeon, April 1979, 29 – 40. Marshall, B., & Alison, L. J. (2006). Structural behavioural analysis as a basis for discriminating between genuine and simulated rape allegations. Journal of Investigative Psychology and Offender Profiling, 3, 21 – 34. Norton, & Grant, T. (2006). Rape myth in true and false rape allegations. Unpublished manuscript. Rainbow, L. (1996). False rape allegations: First steps in a multidimensional approach to the detection of deception in rape statements. Unpublished MSc thesis. University of Surrey. Sleath, E., & Bull, R., (2012). Comparing rape victim and perpetrator blaming in a police officer sample: Difference between specially trained and non-trained officers. Criminal Justice and Behavior, 39,642-661.

  16. Theilade, P. & Thomsen, J. L. (1986). False allegations of rape. Police Surgeon, 30, 17 – 22. Thornhill, R. & Palmer, C. T. (2000). A natural history of rape: Biological bases of sexual coercion. London: MIT Press. Walby, S. & Allen, P. (2004). Interpersonal violence: Findings from 2001 British Crime Survey. Home Office Research Study 276. London: Home Office. Woodhams, J. & Grant, T. (2004). Statements of truth and deception: Using rapists’ language to contrast maintained as true and withdrawn as false rape allegations. Unpublished manuscript.

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