Bethany Growns

Lecturer

University of Canterbury

New Zealand

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Bethany Growns is a Lecturer at the University of Canterbury, New Zealand. Her research areas encompass individual differences in statistical learning and visual comparison abilities, as well as the intersection of mental health and forensic sciences. Recent publications include studies on perceptual expertise, the implications of wrongful convictions, and the role of digital evidence in defense practice.

Bethany Growns

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Articles (16)

Individual differences in distributional statistical learning: Better frequency “discriminators” are better “estimators”

Understanding ‘error’ in the forensic sciences: A primer

Domain‐General Individual Differences in Visual Comparison: Generalisability and Stability of Visual Comparison Ability Re‐Visited

Jack of all trades, master of one: domain-specific and domain-general contributions to perceptual expertise in visual comparison

The Post Office Scandal in the United Kingdom: Mental health and social experiences of wrongly convicted and wrongly accused individuals

Correction to: The novel object-matching test (NOM Test): A psychometric measure of visual comparison ability

Finding the perfect match: Fingerprint expertise facilitates statistical learning and visual comparison decision-making.

The novel object-matching test (NOM Test): A psychometric measure of visual comparison ability

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

Digital evidence in defence practice: Prevalence, challenges and expertise

<i>Retracted:</i> Generalisability and stability of visual comparison ability

Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners

The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices

Prevalence estimates as priors: Juror characteristics, perceived base rates, and verdicts in cases reliant on complainant and defendant testimony

Match me if you can: Evidence for a domain-general visual comparison ability

The prevalence effect in fingerprint identification: Match and non‐match base‐rates impact misses and false alarms

Collaborators (4)

Jason Chin

Rebecca K. Helm

Dana Wilson-Kovacs

Gary Edmond

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