Exploring mock-juror evidence interpretation and belief updating within a probability framework
42 mins 17 secs,
615.80 MB,
MPEG-4 Video
640x360,
29.97 fps,
44100 Hz,
1.94 Mbits/sec
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About this item
| Description: |
Martire, K (University of New South Wales)
Wednesday 31st August 2016 - 10:20 to 11:00 |
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| Created: | 2016-09-06 12:16 |
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| Collection: | Probability and Statistics in Forensic Science |
| Publisher: | Isaac Newton Institute |
| Copyright: | Martire, K |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | The examination and evaluation of juror interpretations of evidence presented at trial is well suited to consideration within a probability framework. In particular Bayes Theorem provides a useful method for setting and comparing against ‘normative’ expectations regarding the evaluation of evidence weight. It is also valuable for refining experimental designs in line with the theorem. In this presentation I will review two lines of research applying Bayes Theorem to the belief updating of lay-decision-makers: The first exploring the alignment between expert intentions and lay interpretations of forensic science expert evaluative opinions expressed using numerical and linguistic likelihood ratios; the second examining juror sensitivity to evidence relevance in the assessment of expert testimony. Some benefits and limitations of the application of a probability frameworks to these issues will be discussed. |
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| MPEG-4 Video * | 640x360 | 1.94 Mbits/sec | 615.80 MB | View | Download | |
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