Concerns have been growing about the veracity of psychological research. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions, or attempt to replicate prior research, in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time-limited), efficient (in terms of re-using structures and principles for different projects), decentralized, diverse (in terms of participants and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside of the network). The PSA and other approaches to crowdsourced psychological science will advance our understanding of mental processes and behaviors by enabling rigorous research and systematically examining its generalizability.

Concerns have been growing about the veracity of psychological research. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions, or attempt to replicate prior research, in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time-limited), efficient (in terms of re-using structures and principles for different projects), decentralized, diverse (in terms of participants and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside of the network). The PSA and other approaches to crowdsourced psychological science will advance our understanding of mental processes and behaviors by enabling rigorous research and systematically examining its generalizability.

Willia m s, Gl e n n P., P a n a yo t ov, Nikol ay a n d Ke m p e , Ver a (2 0 2 0) H o w Do e s Dial e c t Ex p o s u r e Affec t Le a r ni n g t o R e a d a n d S p ell? An Artifici al O r t h o g r a p h y S t u dy. Jou r n al of Ex p e ri m e n t al P syc h olo gy: G e n e r al. IS S N 0 0 9 6-3 4 4 5 Do w nlo a d e d fro m: h t t

Recent research highlights the influence of (e.g., task) context on conceptual retrieval. In order to assess whether conceptual representations are context-dependent rather than static, we investigated the influence of spatial narrative context on accessibility for lexical-semantic information by exploring competition effects. In two visual world experiments, participants listened to narratives describing semantically related (piano-trumpet; Experiment 1) or visually similar (bat-cigarette; Experiment 2) objects in the same or separate narrative locations while viewing arrays displaying these (“target” and “competitor”) objects and other distractors. Upon re-mention of the target, we analysed eye movements to the competitor. In Experiment 1, we observed semantic competition only when targets and competitors were described in the same location; in Experiment 2, we observed visual competition regardless of context. We interpret these results as consistent with context-dependent approaches, such that spatial narrative context dampens accessibility for semantic but not visual information in the visual world.

Some of the findings reported here were presented at the 21 st and 23 rd annual Architectures and Mechanisms for Language Processing (AMLaP) conferences. Word count (excluding tables, figures, references, and appendices): 11,812.