Search

In this study we ask if 4- to 7-year-old children leverage information about object preference and competition to make inferences about where people will store their object.

The aim of this study is to examine how 16 to 18-month-old infants reason about ownership. In particular, we are interested in whether infants this age can identify objects belonging to others using verbal cues and whether they use ownership to reason about people’s emotional reactions to events involving property. That is, do infants have an understanding of ownership and the rights it confers, and thus expect people to react negatively when their property is taken by others without permission?

Poster presentation at Brain Cognition Emotions & Music virtual conference in May 2020. Scroll down for a link to the pdf poster as well as a video recording of the presentation.

Zoom link: https://ucsd.zoom.us/j/92330852612 Thanks for your interest in my poster! Please feel free to stop by on Zoom on 5/20 (Wed) 2:45pm-3:30pm BST. Looking forward to meeting you all :)

People expect others to take efficient paths toward goals. Inefficiency changes how we categorize actions, leading us to see actions as play (Chu & Schulz, 2020), or as movements performed for their own intrinsic value (Schachner & Carey, 2013). Here we find that performing actions for their own value (e.g., aesthetic value), versus for instrumental purposes, provides social information about others. In a pre-registered experiment (N=360), participants judged which character in a pair was more compassionate, or more selfish/manipulative. For one key pair (among distractors), both characters performed the same activity (music, painting, eating, exercising, math, being in nature), and we manipulated why: Either for its own aesthetic value, or as a means-to-an-end (instrumental value). Across all activities, aesthetically-motivated characters were judged as more compassionate and less selfish/manipulative than instrumentally-motivated characters (p’s

Listening to music activates representations of movement and social agents. Why? We ask whether high-level causal reasoning about how music was generated can lead people to link musical sounds with animate agents. To test this, we asked whether people (N=60) make flexible inferences about whether an agent caused musical sounds, integrating information from the sounds’ timing and from the visual context in which it was produced. Using a 2x2 within-subject design, we found evidence of causal reasoning: In a context where producing a musical sequence would require self-propelled movement, people inferred that an agent had been present causing the sounds. When the context provided an alternative possible explanation, this ‘explained away’ the agent, reducing the tendency to infer an agent was present for the same acoustic stimuli. People can use causal reasoning to infer whether an agent produced musical sounds, suggesting that high-level cognition can link music with social concepts.

Human-made objects (artifacts) often provide rich social information about the people who created them. We explore how people reason about others from the objects they create, characterizing inferences about when social transmission of ideas (copying) has occurred. We test whether judgments are driven by perceptual heuristics, or structured explanation- based reasoning. We develop a Bayesian model of explanation-based inference from artifacts and a simpler model of perceptual heuristics, and ask which better predicts people’s judgments. Our artifact-building task involved two characters who built toy train tracks. Participants viewed pairs of tracks, and judged whether copying had occurred. Our explanation-based model accurately predicted on a trial-by- trial basis when participants inferred copying; the perceptual heuristics model was significantly less accurate. Efficient design ‘explained away’ similarity, making similarity weaker evidence of copying for efficient tracks. Overall, data show that like intuitive archeologists, people make rich explanation-based inferences about others from the objects they create.

Recent reports have suggested that many published results are unreliable. To increase the reliability and accuracy of published papers, multiple changes have been proposed, such as changes in statistical methods. We support such reforms. However, we believe that the incentive structure of scientific publishing must change for such reforms to be successful. Under the current system, the quality of individual scientists is judged on the basis of their number of publications and citations, with journals similarly judged via numbers of citations. Neither of these measures takes into account the replicability of the published findings, as false or controversial results are often particularly widely cited. We propose tracking replications as a means of post-publication evaluation, both to help researchers identify reliable findings and to incentivize the publication of reliable results. Tracking replications requires a database linking published studies that replicate one another. As any such database is limited by the number of replication attempts published, we propose establishing an open-access journal dedicated to publishing replication attempts. Data quality of both the database and the affiliated journal would be ensured through a combination of crowd-sourcing and peer review. As reports in the database are aggregated, ultimately it will be possible to calculate replicability scores, which may be used alongside citation counts to evaluate the quality of work published in individual journals. In this paper, we lay out a detailed description of how this system could be implemented, including mechanisms for compiling the information, ensuring data quality, and incentivizing the research community to participate.