Auke Rijpma

How Important Were Formalized Charity and Social Spending Before the Rise of the Welfare State? A Long‐Run Analysis of Selected Western European Cases, 1400–1850

Poor relief in the pre‐industrial period is a much‐investigated topic, but we still lack an idea of its quantitative importance and development, especially in a comparative perspective. This article estimates the magnitude of the various kinds of formalized relief for three present‐day countries (Italy, England, and the Netherlands) in the very long run (1400–1850). The results show that in this period a substantial share of GDP, up to 3 per cent, could be spent on formal relief, offering subsistence to up to 8–9 per cent of the population, with a gradual rise over time and the highest figures being reached in the Netherlands in the eighteenth century. The three cases show a steep decline around 1800, a pattern found more generally in Europe. Next, these results are placed in a broader geographical perspective. This highlights the sharp differences within countries - which could be even larger than those between countries - and the high levels reached in the regions bordering the southern shores of the North Sea. In the last section, the results are used to discuss the possible causes underlying these long‐run patterns and geographical differences, including urbanization, wealth, religion, and social‐organizational features.

Blood is Thicker Than Water: Geography and the Dispersal of Family Characteristics Across the Globe

This article introduces a new dataset of historical family characteristics based on ethnographic literature. The novelty of the dataset lies in the fact that it is constructed at the level of the ethnic group. To test the possibilities of the dataset, we construct a measure of family constraints on women’s agency from it and explore its correlation to a number of geographical factors.

An ecosystem for Linked Humanities Data

The main promise of the digital humanities is the ability to perform scholarly studies at a much broader scale, and in a much more reusable fashion. The key enabler for such studies is the availability of sufficiently well described data. For the field of socio-economic history, data usually comes in a tabular form. Existing efforts to curate and publish datasets take a top-down approach and are focused on large collections. This paper presents QBer and the underlying structured data hub, which address the long tail of research data by catering for the needs of individual scholars. QBer allows researchers to publish their (small) datasets, link them to existing vocabularies and other datasets, and thereby contribute to a growing collection of interlinked datasets. We present QBer, and evaluate our first results by showing how our system facilitates three use cases in socio-economic history.

Testing Todd and Matching Murdock: Global Data on Historical Family Characteristics

ABSTRACT This paper investigates the possibilities for the creation of a global dataset on family and household characteristics. This is done by scrutinizing and comparing two prominent data sources on family system classifications. We first focus on historical data, by comparing Emmanuel Todds classification of countries by family systems with ethnographic data compiled in George Murdocks Ethnographic Atlas. Qualitative and quantitative tests show that the two datasets frequently agree about family traits. Nonetheless, substantial differences exist that are mostly attributable to the focus of the datasets on different regions, and the difficulties in translating local, descriptive studies to hard data. We therefore emphasize that it is important to know the strengths and weaknesses of the two datasets and emphasize that robustness checks are necessary in empirical research into family characteristics. We also compare these historical data with present-day data. This comparison suggests that family characteristics and the values associated with them can persist over long periods.

The dataLegend ecosystem for historical statistics

The main promise of the digital humanities is the ability to perform scholarly studies at a much broader scale, and in a much more reusable fashion. The key enabler for such studies is the availability of sufficiently well described data. For the field of socio-economic history, data usually comes in a tabular form. Existing efforts to curate and publish datasets take a top-down approach and are focused on large collections, produce scarce metadata, require expertise for effective integration, provide poor user support while producing mappings, and present issues at data access. This paper presents the datalegend platform, which addresses the long tail of research data by catering for the needs of individual scholars. datalegend allows researchers to publish their (small) datasets, link them to existing vocabularies and other datasets, and thereby contribute to a growing collection of interlinked datasets. We present the architecture of datalegend; its core vocabularies and data; and QBer, an interactive, user supportive mapping generator and RDF converter. We evaluate our results by showing how our system facilitates use cases in socio-economic history.

Introducing the Historical Gender Equality Index

ABSTRACT Despite recent progress, women are still disadvantaged by their greater domestic labor commitments and impaired access to well-paid jobs; and, in extreme cases, denied the right to live. This has consequences for the well-being of individuals and economic development. Although tools to evaluate country performance in gender equality, especially composite indicators, have been developed since the 1990s, a historical perspective is lacking. This study introduces a composite index of gender equality covering 129 countries from 1950 to 2003. This index measures gender equality in four dimensions (socioeconomic, health, household, and politics). The index shows substantial progress in gender equality, though there is little evidence that less gender-equal countries are catching up. Goldins “quiet revolution” hypothesis is tested as an explanation for this observation, but fails to provide a good explanation. Rather, the long-term institutional and historical characteristics of countries are the main obstacles to convergence.