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Student Poster Award 2024

The EAPL Student Society will be awarding a student poster award to the best student poster (€200) during this year’s EAPL 2024 conference.

To be considered for this award, you have to:

  • present a poster at the EAPL 2024,
  • be the first author of the presented study,
  • be either a Bachelor’s student, Master’s student or PhD student,
  • be a current member of the EAPL (update/renew your membership here!),
  • sign up for award consideration by sending an e-mail to eaplstudent@gmail.com including a PDF of your poster by June 23rd, 2024.

The award is based on reviewer ratings; the student with the highest reviewed submission receives the award. The form below will be used by reviewers from the EAPL-S board, rating the design, content and presentation. At least two board members will independently review each submitted poster. The winner of the poster award will be announced before the conference on July 8th, 2024 to ensure that conference attendees have a chance to attend the presentation of the outstanding awarded student poster.

Download the evaluation criteria here: Poster Evaluation.

Winner Poster Award 2023

Tia Bennett
University of Birmingham

I’m an ESRC-funded 2nd year PhD student at the University of Birmingham, working with Dr Melissa Colloff and Professor Heather Flowe in theApplied Memory Lab. My PhD is in collaboration with the National VIPER Bureau who help to facilitate the construction of lineups in England, Scotland, and Wales. My research aims to determine how identification officers in the UK should construct lineups to maximise discriminability, with a particular focus on optimal suspect-filler lineup similarity.

Abstract: Police lineups usually consist of one suspect and multiple fillers; fillers are people who match the physical description of the suspect but are known innocents. Currently, there is no consensus regarding the ‘optimal’ level of suspect-filler similarity. However, recent research grounded in diagnostic-feature-detection theory (Wixted & Mickes, 2014) suggests that to maximise witnesses’ ability to discriminate between innocent and guilty suspects, lineups should consist of fillers who match the witness’ description, but otherwise look dissimilar to the suspect (Colloff et al., 2021). To investigate the effect of suspect-filler similarity on eyewitness discriminability, we used a multiple trial simultaneous lineup task. Participants (N = 646) were presented with 6 randomly selected to-be-remembered target faces – each of a different physical description – and were asked to identify each face from 6 photo lineups. Half of the lineups contained the target, and the remaining half contained a medium-similarity target replacement. Lineups were randomly generated to contain fillers that were either low, medium, or high similarity to the target or target-replacement. Similarity measurements for each face pair were obtained using a separate spatial arrangement task. Unexpectedly, we found that discriminability decreased with lower similarity. Upon further exploration, we discovered that due to lineup randomisation, the suspect stood out in some lineups due to lighting and physical description issues. To understand whether this a theory issue or an experimental design issue, we plan to run a second experiment with stricter parameters on the filler pool (e.g., all faces would be ‘reasonably described’ in the same way) to ensure that all lineups are fair, and accurately represent low, medium, or high similarity.