That's Not Fair: Children's Neural Computations of Fairness and Their Impact on Resource Allocation Behaviors and Judgments

Autor/inn/en	Cowell, Jason M.; Sommerville, Jessica A.; Decety, Jean
Titel	That's Not Fair: Children's Neural Computations of Fairness and Their Impact on Resource Allocation Behaviors and Judgments
Quelle	In: Developmental Psychology, 55 (2019) 11, S.2299-2310 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0012-1649
DOI	10.1037/dev0000813
Schlagwörter	Resource Allocation; Justice; Moral Values; Moral Development; Physiology; Children; Bias; Neurology; Medicine; Child Behavior; Childrens Attitudes + Suchen Sie Ihr Suchwort? Ressourcenallokation; Gerechtigkeit; Moral value; Ethischer Wert; Moralische Entwicklung; Physiologie; Child; Kind; Kinder; Neurologie; Medizin
Abstract	The ability to distinguish between mere equality in resource distributions and fairness based on a broader range of contextual factors is of paramount importance in social decision making and is a critical component of morality. Children's developmental shift from viewing inequality as a dichotomous moral issue toward a more nuanced understanding of partial inequality has been well documented across middle childhood and is attributed to a host of potential theoretical underpinnings, including developing number concept, increased regard for one's social status, and a maturing concept of fairness. The current study examined the electrophysiological markers associated with children's (N = 83; 4 to 8 years of age) third-party evaluations of equal, slightly unequal, and extremely unequal resource distributions, documenting the timing of fairness considerations. It further explored the link between individual differences in these neural computations and children's allocation behaviors and judgments. Event-related potentials demonstrated an early differentiation between equality and any type of inequality reflected by a medial frontal negativity. Later (after 500 ms), extreme inequality was discriminated from equality and slight inequality. Differences in later waveforms predicted sharing and third-party contextual resource distributions, accounting for wealth and merit. These results illuminate the multifaceted nature of developing neural computations of fairness and illustrate the value of a multiple levels of analysis approach in contributing theoretical clarity toward the developmental science of moral cognition and behavior. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01