This article is concerned with analyzing the occupational attainment of American Jewish men compared to other free men in the mid-19th century to help fill a gap in the literature on Jewish achievement. It does this by using the full count (100 percent) microdata file from the 1850 Census of Population, the first census to ask about the occupation of free men. Independent lists of surnames are used to identify men with a higher probability of being Jewish. These men were more likely than others to be managers, salesmen, and craft workers, and were less likely to be farmers and laborers. The Jewish men have a higher occupational income score on average. In the multiple regression analysis, it is found that among Jewish and other free men, occupational income scores increase with age (up to about age 43 for all men), literacy, being married, having fewer children, being native-born, living in the South, and living in an urban area. Even after controlling for these variables that impact the occupational income score, Jews have a significantly higher score, which is equivalent to about the size of the positive effect of being married. Similar patterns are found using the Duncan Socioeconomic Index. This higher occupational status is consistent with patterns found elsewhere for American Jews in the eighteenth century and throughout the twentieth century.

Staged Fontan pathway treatment is a recognised surgical approach for managing congenital heart lesions with single ventricle physiology. Some patients necessitate communication between the tunnel and the atrium to maintain circulatory balance. During follow-up, adjustments to fenestration size may be required. While methods for enlarging or completely closing fenestrations are common, partially reducing flow through a fenestration remains challenging. We present an effective technique for partially reducing the size of a large, stented fenestration using a coronary stent and a vascular occluder.

The discourse of music reflects historical and cultural changes, interwoven with a multitude of social dynamics. Beyond lyrics, music—through voices and performance—conveys gender stereotypes, often legitimised through repetition. This article examines the construction of voice in Kerala’s popular music, tracing the evolution of the gender stereotyping of voice across three distinct phases: from the period of social dramas following the advent of film music to film music at the beginning of the 21st century. A discourse analysis approach is employed to explore how gendered vocal expressions are shaped and transmitted through popular music culture. Qualitative interviews with practitioners and music experts supplement the analysis, offering deeper insight into Kerala’s sonic landscape and the ways in which music participates in the cultural construction of gender.

A couple of years ago, a non-mathematician friend of mine who takes an interest in mathematics mainly as puzzles mentioned a problem of Euler.

There remain important questions about how personality shapes risk perceptions, willingness to engage in protective behaviors, and policy preferences during a changing pandemic. Focusing on the Big-5 and COVID-19 attitudes, we find associations between risk perceptions and negative emotionality and agreeableness, as well as between each Big-5 trait and protective behaviors and support for government restrictions. These associations are mostly stable over time, with instability pronounced for lockdown policy support, where agreeableness and conscientiousness diminish in importance as pandemic conditions improve. Negative emotionality, conscientiousness, and agreeableness reduce differences between the political left and right and between those who do and do not trust experts. We highlight the heterogeneous interplay between personality and political ideology to understand pandemic policy support, attitudes, and behaviors.

Computing mathematical expectation for an experiment involving a finite number of numerical outcomes is straightforward. Let X denote the random variable having n possible values x1, x2, x3,…, xn. Letting pk denote the probability of xk, the expected value of X is

$$E\,(X)\, = \,\sum\limits_{k\, = \,1}^n {{x_k}{p_k}} ,$$

which can be interpreted as a weighted average of all xk, where the weight of each outcome is represented by its probability. But caution is required when interpreting the sum if there are infinitely many outcomes and the series fails to converge absolutely.