Human factors in forensic science: The cognitive mechanisms that underlie forensic feature-comparison expertise

After a decade of critique from leading scientific bodies, forensic science research is at a crossroads. Whilst emerging research has shown that some forensic feature-comparison disciplines are not foundationally valid, others are moving towards establishing reliability and validity. Forensic examiners in fingerprint, face and handwriting comparison disciplines have skills and knowledge that distinguish them from novices. Yet our understanding of the basis of this expertise is only beginning to emerge. In this paper, we review evidence on the psychological mechanisms contributing to forensic feature-comparison expertise, with a focus on one mechanism: statistical learning, or the ability to learn how often things occur in the environment. Research is beginning to emphasise the importance of statistical learning in forensic feature-comparison expertise. Ultimately, this research and broader cognitive science research has an important role to play in informing the development of training programs and selection tools for forensic feature-comparison examiners

The effects of dams on longitudinal variation in river food webs

We examined the effects of two dams on longitudinal variation of riverine food webs using stable isotope and gut contents analyses along four rivers in the Hunter Valley in eastern Australia. Longitudinal 15N enrichment was observed in most invertebrate taxa and food sources but significant longitudinal variation was rare for 13C, and composition of gut contents of invertebrate taxa did not vary significantly with longitudinal position. Most invertebrates and food sources were more 15N-enriched at sites immediately downstream of the dams than expected from their upstream longitudinal position, a result not mirrored by gut contents and 13C. Enrichment of 15N downstream may be attributed to altered water quality as a result of impoundment but further research is necessary to elucidate whether physico-chemical riverine processes or trophic mechanisms are responsible. Our observations regarding the influence of dams on isotope ratios are contrary to the few existing studies, suggesting the small volumes relative to annual inflows of dams in the present study limit downstream impacts by maintaining aspects of flow variability. © 2013 © 2013 Taylor & Francis

Predicting and projecting memory: Error and bias in metacognitive judgments underlying testimony evaluation

This is the final version. Available on open access from Wiley via the DOI in this recordPreregistration, data, and materials underlying the proposed work are available on OSF at: https://osf.io/ms3f4/?view_only=f6ddb94b127045b1b3b7a487bbe8d874Purpose: Metacognitive judgments of what another person would remember had they experienced a stimulus – i.e., social metamemory judgments, are likely to be important in evaluations of testimony in criminal and civil justice systems. This paper develops and tests predictions about two sources of error in social metamemory judgments that have the potential to be important in legal contexts – errors resulting from beliefs informed by own memory being inappropriately applied to the memory of others, and errors resulting from differential experience of an underlying stimulus. Method: We examined social metamemory judgments in two experimental studies. In Experiment 1 (N = 323) participants were required to make either social metamemory judgments relating to faces or predictions relating to their own memory for faces. In Experiment 2 (N = 275), we manipulated participant experience of faces, holding the described experience of the person whose memory was being assessed constant and asked participants to make social metamemory judgments. Results: As predicted, judgments relating to the memory of others were prone to inaccuracy. While participants making predictions relating to their own memory performed above chance, participants making social metamemory judgments performed no better than chance. Social metamemory judgments were also influenced by the way stimuli were experienced by an assessor, even where this experience did not correspond to the experience of the person whose memory they were assessing. Conclusions: Having our own experiences of memory does not necessarily make us well-placed to assess the memory of others and, in fact, our own experiences of memory can even be misleading in making judgments about the memory of others.UK Research and Innovatio

Prevalence Estimates as Priors: Juror Characteristics, Perceived Base Rates, and Verdicts in Cases Reliant on Complainant and Defendant Testimony

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordData availability: Preregistration, data, and materials underlying this paper are available at https://osf.io/ayp6kJurors often have to make decisions about whether they believe a complainant's or defendant's account of an event. However, the relative ambiguity of cues in testimony creates a situation where juror evaluations can vary significantly. As a result, in cases heavily reliant on testimony there is a particular likelihood that juror characteristics will be associated with verdicts, and it is important to understand these associations. This research investigates the relationships between two juror characteristics – gender and cultural worldviews – and verdicts in two such cases, and the potential for those relationships to be explained by differences in perceived prevalence of alleged events acting as prior probability judgments. As predicted, results show significant relationships between gender and cultural worldview and verdicts and show that these relationships are mediated by differences in underlying prevalence estimates. These findings have important implications for understanding associations between juror characteristics and verdicts and related policy.UKR

Forensic feature-comparison expertise: Statistical learning facilitates visual comparison performance

Forensic feature-comparison examiners in select disciplines are more accurate than novices when comparing samples of visual evidence. This article examines a key cognitive mechanism that may contribute to this superior visual comparison performance: the ability to learn how often stimuli occur in the environment (distributional statistical learning). We examined the relationship between distributional learning and visual comparison performance and the impact of training on the diagnosticity of distributional information in visual comparison tasks. We compared performance between novices given no training (uninformed novices; n = 32), accurate training (informed novices; n = 32), or inaccurate training (misinformed novices; n = 32) in Experiment 1 and between forensic examiners (n = 26), informed novices (n = 29), and uninformed novices (n = 27) in Experiment 2. Across both experiments, forensic examiners and novices performed significantly above chance in a visual comparison task in which distributional learning was required for high performance. However, informed novices outperformed all participants, and only their visual comparison performance was significantly associated with their distributional learning. It is likely that forensic examiners' expertise is domain specific and doesn't generalize to novel visual comparison tasks. Nevertheless, diagnosticity training could be critical to the relationship between distributional learning and visual comparison performance

Distributional statistical learning: How and how well can it be measured?

Item does not contain fulltextIndividuals are readily able to extract and encode statistical information from their environment (or statistical learning). However, the bulk of the literature has primarily focused on conditional statistical learning (i.e. the ability to learn joint and conditional relationships between stimuli), and has largely neglected distributional statistical learning (i.e. the ability to learn the frequency and variability of distributions). In this paper, we investigate how and how well distributional learning can be measured by exploring the relationship between and psychometric properties of two measures: discrimination judgements and frequency estimates. Reliable performance was observed in both measures across two different distributional learning tasks (natural and artificial). Discrimination judgements and frequency estimates also significantly correlated with one another in both tasks, and performance on all tasks accounted for the majority of variance across tasks (55%). These results suggest that distributional learning can be measured reliably, and may tap into both the ability to discriminate between relative frequencies and to explicitly estimate them.CogSci 2020: 42nd Annual Conference of the Cognitive Science Society (29 July - 1 August 2020

What do the experts know? Calibration, precision, and the wisdom of crowds among forensic handwriting experts

Forensic handwriting examiners currently testify to the origin of questioned handwriting for legal purposes. However, forensic scientists are increasingly being encouraged to assign probabilities to their observations in the form of a likelihood ratio. This study is the first to examine whether handwriting experts are able to estimate the frequency of US handwriting features more accurately than novices. The results indicate that the absolute error for experts was lower than novices, but the size of the effect is modest, and the overall error rate even for experts is large enough as to raise questions about whether their estimates can be sufficiently trustworthy for presentation in courts. When errors are separated into effects caused by miscalibration and those caused by imprecision, we find systematic differences between individuals. Finally, we consider several ways of aggregating predictions from multiple experts, suggesting that quite substantial improvements in expert predictions are possible when a suitable aggregation method is used.</p