The COVID-19 pandemic has had a huge impact on the world for three and half years, since the end of 2019. A nasty feature of the disease is the existence of numerous (infected) cases without symptoms. It was difficult for society to engage in social/economic activities while avoiding spreading of the disease. The internet played an indispensable role in the fight against the pandemic in many ways. In particular numerous public health date, which one would have never imagined if it were not for the pandemic, were made open to the public through the Internet. In this paper, we discuss a few issues concerning the usage of these open data in policy-making. We consider the following four topics regarding COVID-19: (1) incubation time, (2) the effect of vaccination, (3) estimation of the ratio between actual cases and cases reported by health authorities, and (4) estimation of excessive deaths during the pandemic.

This paper describes shared tasks that use natural language processing techniques to link textual and tabular data, which are treated as unstructured data. Specifically, it describes the shared tasks of finding the basis for the figures and amounts contained in the tables in the minutes of local council meetings and annual securities reports. The local assembly minutes and annual security reports provide data that are expected to be used as primary information. However, publicly available data often consist of unstructured document formats. Therefore, we designed a budget argument mining task, which analyses the argument structure of the minutes, focusing on monetary expressions (amount of money). Furthermore, we designed the shared tasks of text-table relationship extraction and table data extraction. In this paper, we provide an overview of these shared tasks.

One of the challenges in establishing evidence-based policy making (EBPM) is the collection of good quality data that can be used as policy resources. However, the response rates of national and municipal public surveys and most social surveys/public opinion polls in Japan and abroad have declined, and this trend will inevitably continue in the future. In this sense, we believe that it is worthwhile to focus on mail surveys, which remain one of the most commonly used forms of self-administered surveys, in comparison to telephone and online formats, and to explore measures to improve their response rate. Mail surveys are commonly used in all areas of the social sciences, with a significant percentage of Japan’s public opinion polls being conducted via the postal service. While many studies examine tools and techniques to improve survey response rates, it remains unclear which are effective, and the response rates are continuing to decline. In this study, we discuss the effect of several variables expected to influence mail survey response rates.

The evidence addressed in Evidence-Based Policy Making (EBPM) in Japan tends to be biased towards quantitative data. However, the principles of EBPM suggest that evidence derived from qualitative studies should be utilized alongside quantitative research in EBPM. The use of qualitative research in the field of policy research allows for a thorough exploration of the potential for qualitative evidence utilization, which has largely been overlooked in EBPM. This article clarifies the following points: Firstly, qualitative evidence can be utilized as a basis for presenting one of the candidate agendas. Secondly, in the preliminary assessment of policymaking aimed at addressing social issues with a small number of cases, it is necessary to utilize qualitative evidence. Thirdly, it is important to assess uncertainty in qualitative evidence. Finally, this article demonstrates that in qualitative research following statistical methods, the criteria for evaluating uncertainty include ‘Credibility’ and ‘Transferability’, and that ‘Theoretical Saturation’ and ‘Applicability’ can be used as evaluation criteria for qualitative research based on the Grounded Theory Approach.

Customer satisfaction surveys are one type of survey conducted by companies targeting their customers. They are used for a wide range of purposes, such as understanding needs and satisfaction levels regarding the company and its products. Questionnaire surveys are a method that can capture the emotions of the survey targets. By measuring these, it is possible to foresee the future at an early stage. Municipalities also need to capture the feelings and background of residents who want to continue living there rather than just judging the situation by following the actual numbers of residents moving in and out.

When comparing the CS surveys conducted by the private sector and the surveys of residents conducted by municipalities, many similarities can be seen. Private-sector CS surveys have their own methods of surveying, creating questions, analyzing methods, and obtaining results. This know-how can be applied directly to resident surveys conducted by municipalities. This article will explain the methods of CS surveys conducted by private companies, focusing on the know-how that can be applied to resident surveys conducted by municipalities.