Table 2.

WAIC analysis. Best fit model is Model 5.

model	model parameters (DV: subject punished [1=yes])	WAIC (standard error)	difference from lowest WAIC (standard error)	AIC weight
1	Hypothesis: children punish selfish third parties (TPs) and prosocial TPs differently. Fixed effect: Third party behaviour (Selfish TP=1, Prosocial TP=0). Random effect: Actor ID	1441.8 (25.78)	39.5 (14.54)	<0.01
2	Hypothesis: children punish selfish TPs and prosocial TPs differently, and this tendency varies across age. Fixed effects: Third party behaviour × Subject age (centred). Random effect: Actor ID	1430.9 (26.80)	28.6 (12.60)	<0.01
3	Hypothesis: children punish selfish TPs and prosocial TPs differently, and this tendency is influenced by novel normative information about who to punish. Fixed effects: Third party behaviour × Dummies for normative primes (2: dummy for Punish-Selfish TP Prime, dummy for Punish-Prosocial TP Prime; Reference level = Punish-Either Prime). Random effect: Actor ID	1431.8 (27.02)	29.4 (12.32)	<0.01
4	Hypothesis: children punish Selfish TPs and Prosocial TPs differently, this tendency is influenced by normative information, and these effects vary across age. Fixed effects: Third party behaviour × Subject age × Dummies for normative primes (2: dummy for Punish-Selfish TP Prime, dummy for Punish-Prosocial TP Prime; Reference level = Punish-Either Prime). Random effect: Actor ID	1424.6 (28.74)	22.3 (9.76)	<0.01
5	Hypothesis: children punish selfish TPs and prosocial TPs differently, this tendency is influenced by normative information, and these effects vary across both age and societies. Fixed effects: third party behaviour × Subject age × Dummies for normative primes (2: dummy for Punish-Selfish TP Prime, dummy for Punish-Prosocial TP Prime; Reference level = Punish-Either Prime). Random effects: Actor ID, Subject's Society	1402.3 (31.07)	0.00 (n.a.)	∼1.00