The revision of sexist laws is complicated not only by disagreements between progressives and traditionalists but also by opposing views held by different types of traditionalists. We design a two-wave list experiment with information treatments to examine public opinion toward reforming the Japanese monarchy’s male-only patrilineal succession rule, focusing on two strands of traditionalism: conservatism and sexism. We show that conservatism, not sexism, is associated with stronger opposition to the ascension of female monarchs. Moreover, opinions toward gendered succession rules are hard to dislodge, because they are rooted in deep-held values. Treatments that highlight the capability of female heirs, the rarity of current practices in peer nations, and the perils posed by succession crises fail to change respondent preferences. Our study reveals the discordance within traditional values, and how this can impede efforts to reform statutory gender discrimination.

This chapter situates examples of socialist development within wider historical contexts, and discusses their evolution, consequences, and potentials. The state socialist model of development emerged out of a particular historical experience, that of the USSR following the Bolshevik revolution. However, the problems faced by the Bolsheviks were of a general nature, and the industrialization achieved in the USSR thus appeared to offer lessons for other countries attempting to develop and industrialize. But the model proved to be of more limited applicability than had been hoped when applied elsewhere. The rise of China may present an alternative path to many, but the extent to which it is unique and whether it could be characterized as a 'socialist development model' remain controversial. In addition, the reforms in China have been accompanied by many challenges. As the world economy has become more interdependent, the concept of a nationally based socialist road to development has been called into question.

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Conjoint analysis is widely used for estimating the effects of a large number of treatments on multidimensional decision-making. However, it is this substantive advantage that leads to a statistically undesirable property, multiple hypothesis testing. Existing applications of conjoint analysis except for a few do not correct for the number of hypotheses to be tested, and empirical guidance on the choice of multiple testing correction methods has not been provided. This paper first shows that even when none of the treatments has any effect, the standard analysis pipeline produces at least one statistically significant estimate of average marginal component effects in more than 90% of experimental trials. Then, we conduct a simulation study to compare three well-known methods for multiple testing correction, the Bonferroni correction, the Benjamini–Hochberg procedure, and the adaptive shrinkage (Ash). All three methods are more accurate in recovering the truth than the conventional analysis without correction. Moreover, the Ash method outperforms in avoiding false negatives, while reducing false positives similarly to the other methods. Finally, we show how conclusions drawn from empirical analysis may differ with and without correction by reanalyzing applications on public attitudes toward immigration and partner countries of trade agreements.