RESUMO
Opinions on abortion are more polarized than opinions on most other moral issues. Why are some people pro-choice and some pro-life? Religious and political preferences play a role here, but pro-choice and pro-life people may also differ in other aspects. In the current preregistered study (N = 479), we investigated how pro-choice women differ in their moral foundations from pro-life women. When the Moral Foundations Questionnaire (MFQ) was applied (i.e., when declared moral principles were measured), pro-life women scored higher than pro-choice women in loyalty, authority, and purity. However, when women were asked about moral judgments indirectly via more real-life problems from the Moral Foundations Vignettes (MFV), pro-choice women scored higher than pro-life women in emotional and physical care and liberty but lower in loyalty. When we additionally controlled for religious practice and political views, we found no differences between groups in declaring moral foundations (MFQ). However, in the case of real-life moral judgments (MFV), we observed higher care, fairness, and liberty among pro-choice and higher authority and purity among pro-life. Our results show intriguing nuances between women pro-choice and pro-life as we found a different pattern of moral foundations in those groups depending on whether we measured their declared abstract moral principles or moral judgment about real-life situations. We also showed how religious practice and political views might play a role in such differences. We conclude that attitudes to abortion "go beyond" abstract moral principles, and the real-life context matters in moral judgments. Supplementary information: The online version contains supplementary material available at 10.1007/s12144-023-04800-0.
RESUMO
This paper has two aims. First, we investigate how often people make choices conforming to Bayes' rule when natural sampling is applied. Second, we show that using Bayes' rule is not necessary to make choices satisfying Bayes' rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes' rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes' rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes' rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Bayes' rule to apply. It does not require inversion of conditions [transforming P(H) and P(D|H) into P(H|D)] when computing chances. Study 3 examined the efficiency of three fallacious heuristics (pre-Bayesian, representativeness, and evidence-only) in producing choices concordant with Bayes' rule. Computer-simulated scenarios revealed that the heuristics produced correct choices reasonably often under specific base rates and likelihood ratios. Summing up we conclude that natural sampling results in most choices conforming to Bayes' rule. However, people tend to replace Bayes' rule with simpler methods, and even use of fallacious heuristics may be satisfactorily efficient.
