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I analyze factory worker households in the early 1920s in Osaka to examine idiosyncratic income shocks and consumption. Using the household-level monthly panel dataset, I find that while households could not fully cope with idiosyncratic income shocks at that time, they mitigated fluctuations in indispensable consumption during economic hardship. In terms of risk-coping mechanisms, I find suggestive evidence that savings institutions helped mitigate vulnerabilities and that both using borrowing institutions and adjusting labor supply served as risk-coping strategies among households with less savings.

ABSTRACT Exogamous marriage alliances involving royal women played a prominent role in the conversion of the Anglo-Saxon kingdoms to Christianity in the seventh century AD. Yet the large number of well-furnished female burials from this period suggests a broader change in the role of women. The authors present the results of isotopic analysis of seventh-century burials, comparing male and female mobility and the mobility of females from well-furnished versus poorly/unfurnished burials. Results suggest increased mobility during the Conversion Period that is, paradoxically, most noticeable among women buried in poorly furnished graves; their well-furnished contemporaries were more likely to have grown up near to their place of burial.

This study uses proprietary data on environmental and social issue engagement in Japan to examine institutional investors’ selection criteria and the effects of engagement on the environmental and social performance of companies. The results indicate that institutional investors engage with companies that align with their monitoring motivations, exhibit relatively good capital efficiency, and demonstrate good governance practices. Additionally, environmental engagements lead to the adoption of long-term CO2 emission targets and a reduction in companies' CO2 emissions. Social and governance engagement increased the representation of women on corporate boards. These results indicate the presence of differences in the effects of engagements across different themes.

This paper describes the Radiology Report TNM staging (RR-TNM) subtask as a part of NTCIR-17 Medical Natural Language Processing for Social Media and Clinical Texts (MedNLP-SC) shared task in 2023. This subtask focused on automated lung cancer staging based on radiology reports. We created a dataset of 243 Japanese radiology reports containing no personal health information. A total of three teams with 16 members participated and submitted seven solutions. The best accuracy scores for the T, N, and M categories reached 67%, 80%, and 93%, respectively. Through the RR- TNM subtask, we have provided a valuable open Japanese clinical corpus and useful insights to apply natural language processing for secondary usage of staging information.