Juan Botella, Óscar García Leal, Laura Moreno, Shih Pei-Chun, José Santacreu


differentiate at least two different types of interactions: cooperation and competition.
Specifically, several attempts have been made to predict and explain
cooperative behavior. Typically, it has been studied using artificial situations
(e.g. Azrin & Lindsley, 1956; Cohen & Lindsley, 1964; Lindsley, 1966; Mithaug
& Burgess, 1967, 1968; Schmitt, 1987; Schmitt & Marwell, 1968; Shimoff &
Matthews, 1975), being the most typical matrix games like the Prisoner’s
Dilemma, but recent studies have incorporated more naturalistic situations.
Following the research initiated by Ribes-Iñesta (Ribes-Iñesta, 2001; Ribes-
Iñesta & Rangel, 2002) we show how a computerized puzzle-solving task can
be used to improve our knowledge of dyadic interactions, as minimal settings
representative of social behavior. In three studies, the candidates for a job
position could cooperate or not cooperate with another candidate by helping
with the other’s puzzles. Results show that the behaviors could be classified
in three groups: non-cooperation, graded cooperation, and systematic cooperation.
These behavioral tendencies were highly consistent throughout the task and reasonably stable after a one-year interval. Their distribution is not
independent of gender; females show a higher frequency of non-cooperative
behavior than of systematic cooperation, whereas males show the reverse.
These results are in accordance with recent reports in the literature (e.g. Kurzban
& Houser, 2001). As previous studies, we demonstrate that the tendency
to cooperate is influenced by the cooperative tendency of the others.

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