Using three different types of digitized historical sources - one containing structured information, one semi-structured, and one unstructured - we construct a relational database that connects individuals, firms, and textual material related to individuals and firms. The broader project examines the emergence of professional engineering, 1870-1930, and uses the global mining sector as a case study. This paper explains the methods used to construct the initial three constituent datasets, including techniques to clean and validate each. It then explains the methods used to transform and link those datasets, creating a relational database that includes information on roughly 130,000 individuals, over 50,000 firms, and almost 400,000 journal articles. We are able to trace individuals, firms, and technologies over time and space and identify interconnected communities and networks in a globalized setting, which we illustrate in several brief case studies.
Long-run studies of income and wealth distributions based on tabular tax data focus almost exclusively on the top 10% or 1% and do not consider underlying dimensions of social stratification. This paper proposes a methodology which overcomes these limitations by creating multivariate synthetic data through a combination of three techniques: ungrouping, imputations and reweighting. The reliability of the methodology is shown through an evaluation based on modern EU-SILC data. The methodology is then applied to grouped income tax data from the Netherlands between 1950 and 1976. First results show that a narrow focus on the top of the distribution neglects a lot of patterns and trends that shape total income inequality. The multivariate synthetic microdata open up a large scala of research potential.
This article proposes two methods to analyze processual and social dynamics in early modern administration, based on thousands of digitally encoded records from the Vatican Archive concerning 17th-century ecclesiastical office provisions. The Roman Curia as the most wide-reaching center of premodern Church administration was largely bureaucratic and heavily reliant on patronage and nepotism. We introduce two quantitative metrics: 'lead speed,' relating spatial to temporal distances to measure administrative pace; and a 'nepotism probability,' using linguistic comparison of personal names and morphosyntactic markers in the sources within one appointment entry as an indicator of familial provision ties. Aggregating these metrics across thousands of administrative instances reveals evolving patterns of global governance in early modern Catholicism while underscoring the necessity of research into the comparability of locally embedded and possibly varying notions of kinship and distance on a continental or global scale. The article situates the methods historically and explains dataset construction and computational implementation, validates initial results, and shows how the metrics enable systematic analysis of administrative pace understood as efficiency and nepotistic dynamics within established historiographical debates.
The primary purpose of this article is to introduce the Pathological and Anatomical Repository Training Networks (PART Net) database. The database is a collection of information on historic anatomical and pathological collections in Europe and former European colonial holdings. PART Net includes tables with data on 105 institutions currently or formerly holding anatomical and pathological collections, 409 personnel associated with those collections, and the training history of those key personnel (where available). The article also provides analysis of the personnel training networks, identifying key figures in the establishment and promulgation of an international network of anatomy and pathology museums. The analysis points toward Pieter Pauw (1564-1617) and Archibald Pitcairn (1652-1713) as important originary figures in the establishment of this network.
This paper has two main contributions. The first one is to present a new data set with 360 consistent local geographic units (CLGU), defined by matching the departments of each population census in Argentina between 1895 and 2022. This structure generates a traceable and transparent connection between the different ways in which information is presented in each census; hence, it provides a crucial tool to combine information on socioeconomic dimensions across time. The second contribution is the estimation of Local Indices of Economic Activity (LIEA) for 1895 and 1960. Using the 360 CLGUs, the paper offers a novel exploration of the spatial changes in economic activity and local economic growth in Argentina in the first half of the twentieth century.
