My latest paper with Douglas MacFarlance and colleagues, “Reducing Demand for Overexploited Wildlife Products: Lessons from Systematic Reviews from Outside Conservation Science,” has just been accepted for publication in Conservation Science and Practice. The abstract for the paper is below:
Conservationists have long sought to reduce consumer demand for products from overexploited wildlife species. Health practitioners have also begun calling for reductions in the wildlife trade to reduce pandemic risk. Most wildlife-focused demand reduction campaigns have lacked rigorous evaluations and thus their impacts remain unknown. There is thus an urgent need to review the evidence from beyond conservation science to inform future demand-reduction efforts. We searched for systematic reviews of interventions that aimed to reduce consumer demand for products that are harmful (e.g., cigarettes and illicit drugs). In total, 41 systematic reviews were assessed, and their data extracted. Mass-media campaigns and incentive programs were, on average, ineffective. While advertising bans, social marketing, and location bans were promising, there was insufficient robust evidence to draw firm conclusions. In contrast, the evidence for the effectiveness of norm appeals and risk warnings was stronger, with some caveats.
My latest paper with Li Tay, Tim Kurz, and Ullrich Ecker, “A comparison of prebunking and debunking interventions for implied versus explicit misinformation,” has just been accepted for publication in the British Journal of Psychology. The abstract for the paper is below:
Psychological research has offered valuable insights into how to combat misinformation. The studies conducted to date, however, have three limitations. First, pre-emptive (“prebunking”) and retroactive (“debunking”) interventions have mostly been examined in parallel, and thus it is unclear which of these two predominant approaches is more effective. Second, there has been a focus on misinformation that is explicitly false, but misinformation that uses literally true information to mislead is common in the real world. Finally, studies have relied mainly on questionnaire measures of reasoning, neglecting behavioural impacts of misinformation and interventions. To offer incremental progress towards addressing these three issues, we conducted an experiment (N = 735) involving misinformation on fair trade. We contrasted the effectiveness of prebunking versus debunking and the impacts of implied versus explicit misinformation, and incorporated novel measures assessing consumer behaviours (i.e., willingness-to-pay; information seeking; online misinformation promotion) in addition to standard questionnaire measures. In general, we found debunking to be more effective than prebunking, although both were able to reduce misinformation reliance. We also found that individuals tended to rely more on explicit than implied misinformation both with and without interventions.
My latest paper with Adam Osth, “Do item-dependent context representations underlie serial order in cognition?” has just been accepted for publication in Psychological Review. The abstract for the paper is below:
Logan (2021) presented an impressive unification of serial order tasks including whole report, typing, and serial recall in the form of the context retrieval and updating (CRU) model. Despite the wide breadth of the model’s coverage, its reliance on encoding and retrieving context representations that consist of the previous items may prevent it from being able to address a number of critical benchmark findings in the serial order literature that have shaped and constrained existing theories. In this commentary, we highlight three major challenges that motivated the development of a rival class of models of serial order, namely positional models. These challenges include the mixed-list phonological similarity effect, the protrusion effect, and interposition errors in temporal grouping. Simulations indicated that CRU can address the mixed list phonological similarity effect if phonological confusions can occur during its output stage, suggesting that the serial position curves from this paradigm do not rule out models that rely on inter-item associations, as has been previously been suggested. The other two challenges are more consequential for the model’s representations, and simulations indicated the model was not able to provide a complete account of them. We highlight and discuss how revisions to CRU’s representations or retrieval mechanisms can address these phenomena and emphasize that a fruitful direction forward would be to either incorporate positional representations or approximate them with its existing representations.
My latest paper with Graham Hitch and Tom Hartley, “Computational Models of Working Memory for Language” has just been accepted for publication as a book chapter in The Cambridge Handbook of Working Memory and Language edited by John Schwieter and Wen Zhisheng and due to appear in 2022. The abstract for the chapter is below:
We start with a brief review of evidence that verbal working memory (WM) involves a limited capacity phonological loop capable of retaining verbal sequences for a few seconds in immediate serial recall, vocabulary acquisition, speech production and language comprehension. The challenge of explaining how such a system handles information about serial order is discussed in the context of computational models of the immediate recall of unstructured sequences of words, letters, or digits, an extensively studied laboratory task for which there are many benchmark findings. Evaluating computational models against these benchmarks suggests a serial ordering mechanism in which items are simultaneously active before being selected for sequential output by a process of competitive queuing (CQ). Further evidence shows how this process may operate in the context of sequences that conform to various kinds of linguistic constraint. We conclude by suggesting that CQ is a promising theoretical mechanism for connecting and potentially unifying theories of WM and language processing more generally despite major differences in their scope and level of abstraction.
My latest paper with Susie Wang, Zoe Leviston, Iain Walker, and Carmen Lawrence, “Construal Level Theory and Psychological Distancing: Implications for Grand Environmental Challenges” has just been accepted for publication in One Earth. The summary for the paper is below:
Research in social and cognitive sciences has used the Construal Level Theory (CLT) of psychological distance as a framework for understanding environmental challenges such as climate change. This primer reflects on the how psychological distance and construal can help to understand environmental challenges, from the perceptions and social construction of environmental issues as distant and abstract, to implications for decision-making and action towards long-term targets. We also reflect on areas where the theory and concept are less useful, when assuming that psychological distance and construal level can be easily reduced or altered to promote lasting changes to environmental action.