The first paper coming out of my PhD project has just come out!
http://nature.com/articles/s41598-020-74975-0

@DLabMelbourne, @DanFeuerriegel, @dr_simon_laham, @renrutmailliw and I looked at how people update their moral judgements of fairness-related actions as they learn new information.

We asked participants to judge sharing actions of (unknowingly fictional) individuals playing a variant of the Dictator game as Decision-makers (Person C), and update these judgements as they lean contextual information regarding deservingness of Receivers (Person A).

Observing patterns of initial context-absent moral judgement across presented offers we found that participants had different judgement styles, and that these styles were well captured by spline functions (blue).

Similar was true for final, context-present judgements, where information about the Decision-maker’s offer relative to Receiver’s deservingness modulated the judgement patterns.

Context-present judgements were also well captured by spline functions.

We analyzed the curvilinear interindividual variability in these judgement patterns using functional PCA. We interpreted the resulting PCs as indexing relative importance of different moral norms to an individual.

Our findings show that most participants flexibly switched from relying on commonly studied context-independent norms (generosity, equality), to relying on related, context-dependent norms (relative generosity, indirect reciprocity), as they integrate contextual information.

Interestingly, a substantial minority of participants withheld their context-absent judgements of selfishness until receiving contextual information.

I would like to thank my supervision team @DLabMelbourne, @DanFeuerriegel, and @dr_simon_laham as well as @renrutmailliw for their fantastic contribution and helping bring this paper to a standard that I am very proud of!

Materials and code are open and available at https://osf.io/xcbuh/ 

I also thank @DSHunimelb, @Psychunimelb, @EWB_Hub, for providing such a great environment to work and exchange ideas within.

My thanks also extend to @drsmillie, @Todd_A_Hare, @christophwkorn, @AS4SANinc, and @ACNS_Official for having me over to present this paper while it was still in development, and for useful discussions.