The determination of victim credibility by adult and juvenile sexual assault investigators
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DOI: 10.1016/j.jcrimjus.2014.12.001
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References listed on IDEAS
- Jouvenel Bertrand de, 1998. "De La Justice," Journal des Economistes et des Etudes Humaines, De Gruyter, vol. 8(1), pages 127-144, March.
- Franklin, Travis W., 2010. "The intersection of defendants' race, gender, and age in prosecutorial decision making," Journal of Criminal Justice, Elsevier, vol. 38(2), pages 185-192, March.
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- Bouffard, Jeffrey A., 2000. "Predicting type of sexual assault case closure from victim, suspect, and case characteristics," Journal of Criminal Justice, Elsevier, vol. 28(6), pages 527-542.
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Cited by:
- Campbell, Bradley A. & Wells, William & King, William R., 2021. "What happens when sexual assault kits go untested? A focal concerns analysis of suspect identification and police pre-arrest decisions," Journal of Criminal Justice, Elsevier, vol. 76(C).
- Willmott, Dominic & Boduszek, Daniel & Debowska, Agata & Woodfield, Russell, 2018. "Introduction and validation of the Juror Decision Scale (JDS): An empirical investigation of the Story Model," Journal of Criminal Justice, Elsevier, vol. 57(C), pages 26-34.
- Hine, Benjamin & Murphy, Anthony, 2019. "The influence of ‘High’ vs. ‘Low’ rape myth acceptance on police officers' judgements of victim and perpetrator responsibility, and rape authenticity," Journal of Criminal Justice, Elsevier, vol. 60(C), pages 100-107.
- Lovell, Rachel & Luminais, Misty & Flannery, Daniel J. & Bell, Richard & Kyker, Brett, 2018. "Describing the process and quantifying the outcomes of the Cuyahoga County sexual assault kit initiative," Journal of Criminal Justice, Elsevier, vol. 57(C), pages 106-115.
- Hine, Benjamin & Murphy, Anthony, 2017. "The impact of victim-perpetrator relationship, reputation and initial point of resistance on officers' responsibility and authenticity ratings towards hypothetical rape cases," Journal of Criminal Justice, Elsevier, vol. 49(C), pages 1-13.
- Lovell, Rachel E. & Klingenstein, Joanna & Du, Jiaxin & Overman, Laura & Sabo, Danielle & Ye, Xinyue & Flannery, Daniel J., 2023. "Using machine learning to assess rape reports: “Signaling” words about victims' credibility that predict investigative and prosecutorial outcomes," Journal of Criminal Justice, Elsevier, vol. 88(C).
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