At the time of her death in October 2002, Dr. Tamara Hareven was in the process of completing a large cross-cultural examination of the global declines in the silk and textile industries. A small sample of her interview data transcripts from canuts in Lyon have, more than 20 years after her death, been translated into English and coded for themes as a pilot study of a larger data set. Six themes emerged from the participants' data. Participants sensed that the industry was disappearing, that the industry was something that was looked at as a historical artifact to be studied rather than a profession, and that there was not enough being done to encourage young people to enter the industry. Gender disparities within the industry continued to a lesser extent than before the 20th century began, but still seemed profound, especially as girls who were recruited for apprenticeships were often minors when they were moved away from their families. The apprenticeship conditions continued to be less than desirable well into the 20th century. Economically, the silk industry is often poorly paid and vulnerable to economic crises as fashion and world economics change. Large social changes often had impacts on the family life of the silk worker families. Finally, just as economics tended to ebb and flow for the silk industry, so did the labor conditions.

This paper examines the causes of infant mortality for the Hanseatic city of Rostock, Germany, between 1800 and 1904. Based on unique individual-level church records from Rostock's largest inner-city parish, St. Jakobi, we apply the novel ICD10h coding system for the first time to the German context. Using this coding system, we analyse cause-specific patterns of infant, neonatal and post-neonatal mortality in an internationally comparable way and bring new insights into the determinants of 19th-century infant mortality, which was shaped by increase and stagnation in wide parts of Germany. Our results show that Rostock experienced a stagnating infant mortality rate at a low level in international comparison during the first 40 years of the 19th century, followed by severe increases during the next 20 years and a stage of slight decline and stagnation towards the end of the study period. This suboptimal development from 1840 was strongly related to post-neonatal mortality and causes of death that are related to unfavourable sanitary conditions and/or poor nutrition, which possibly hints at worsening housing and living conditions following accelerated population growth. Our analyses also reveal that water-food borne diseases were underestimated in Rostock, even though symptomatic disease terms such as convulsions and teething, that were frequently recorded over much of the 19th century, had deviating seasonality patterns and thus cannot entirely refer to this disease group but rather to a wide field of different diseases. The applied coding scheme is a significant step forward to foster comparative international research on historical cause-specific mortality.

Any machine learning method for transcribing historical text requires manual verification and correction, which is often time-consuming and expensive. Our aim is to make it more efficient. Previously, we developed a machine learning model to transcribe 2.3 million handwritten occupation codes from the Norwegian 1950 census. Here, we manually review the 90,000 codes (3%) for which our model had the lowest confidence scores. We allocated these codes to human reviewers, who used our custom annotation tool to review them. The reviewers agreed with the model's labels 31.9% of the time. They corrected 62.8% of the labels, and 5.1% of the images were uncertain or assigned invalid labels. 9,000 images were reviewed by multiple reviewers, resulting in an agreement of 86.4% and a disagreement of 9%. The results suggest that one reviewer per image is sufficient. We recommend that reviewers indicate any uncertainty about the label they assign to an image by adding a flag to their label. Our interviews show that the reviewers performed internal quality control and found our custom tool to be useful and easy to operate. We provide guidelines for efficient and accurate transcription of historical text by combining machine learning and manual review. We have open-sourced our custom annotation tool and made the reviewed images open access.

In this new editorial of Historical Life Course Studies key shifts are discussed. We welcome Joana Maria Pujadas-Mora as new co-editor in chief and Eva van der Heijden as associate editor. We thank Luciana Quaranta for her contributions to the development of the journal. Over the past years, Historical Life Course Studies has experienced substantial growth in terms of output and impact. The journal got indexed in Scopus and an application for admission to the Web of Science is pending. Social media engagement and upcoming video releases further enhance the journal's outreach. Gratitude extends to sponsors for Diamond Open Access support, as well as to all authors, reviewers, and readers who jointly contribute to the success of Historical Life Course Studies. The editors look with confidence to the future and hope to welcome many submissions over the next years.

Historical demography is generally concerned with the changing economic, social and normative contexts of human behaviour and health outcomes. To most historical demographers, the 'genetic' component of behaviour and health is either unknown or assumed to be constant. However, several studies point at the shift over time in the relative importance of environment and genes: in periods and social groups with strong normative or economic constraints on behaviour, the 'genetic potential' is often not realized. Therefore, to some extent, the waning of environmental constraints on heritability plays a role in changes in demographic outcomes over time. Determining the relative importance of heritability versus shared environment in historical populations for which only genealogies are available poses a challenge. Kin may live in different periods, and in different cultural and social settings. This explorative paper analyses the association between heights of conscripted relatives, as well as their life span. I estimate how the associations are affected by respectively genetic relatedness, shared historical period and shared social and geographical environment. Furthermore, I make a distinction between kin related via the mother versus kin related via the father. All kinds of kin are involved in the analysis: (half, full and twin) brothers, fathers, grandfathers, uncles and cousins. The data consist of about 3,000 men culled from Texel island genealogies, which also include descendants of families who had left the island. Life span has a weak, but still discernible, genetic element. The heritability of height is much stronger, especially at age 19/20. The correlations of mother’s kin with her son's heights are stronger than those of her husband's kin. The analysis does not yield a consistent effect of a protective environment on kin correlations in either height or life span.

Based on unique individual-level cause of death data, this article presents an analysis of the development of infant mortality and the underlying cause of death pattern in the city of Amsterdam in the period 1856–1904. We contribute to the discussion on the development of infant mortality and its determinants and test the newly-constructed ICD10h coding system. First, our results demonstrate that the ICD10h and groupings of causes worked quite well for our period and city data. Second, Amsterdam moved from being one of the most lethal cities in the country to one of the healthiest for infants. These improvements in the fate of infants were brought about despite faltering progress in the provision of piped water, and an absence of modern sewerage throughout the period. For the entire period air-borne diseases were a prominent cause of death category, peaking in the 1880s and still making up the major group of diseases by 1904. Water- and food related ailments were also dominating the epidemiological pattern after the 1870s. Vague or ill-defined disease terms were frequent at the start of the study period. These observations suggest that physicians were increasingly better able and more prepared to formulate more precise disease terms by the 1900s. The seasonality analysis of the different disease groups demonstrates strong summer effects on the group of water- and food related causes of death. It testifies to the shortcomings in the city’s hygienic situation and limited breastfeeding.

In recent years the development of historical databases reconstructing the lives of large populations accelerated. These considerable investments of time and money have greatly expanded possibilities for new research in history, demography, sociology, economics, and other disciplines. This special issue describes the content and design of 23 important historical databases. Authors were given the freedom to discuss a range of practical and technical decisions from evaluating archival sources to crowdsourcing data entry. The most common issue is nominative record linkage, but we find different choices between semi-automatic and fully automatic linkage techniques and various approaches for connecting diverse sources. Some databases describe special problems, like linking Chinese names, handwritten text recognition or the construction of a release in IDS-format. Other databases offer detailed descriptions of sources or discuss prospects for including new datasets.

The Geneva databases are a data resource covering the period 1800–1880 for the city of Geneva, and occasionally the canton of Geneva. The research team adopted an alphabetical sampling approach, collecting data on individuals whose surname begins with the letter B. The individuals and households belonging to this sample in six population censuses between 1816 and 1843 were digitised and linked. A second database collected marriage and divorce records for the period 1800–1880. A third collection of data included residence permits. All these sources were used for a massive reconstitution of families. This article presents the sources, the linking methods, the typologies used to code places and occupations, to study household structures and forms of solitude. Combined with qualitative information extracted from the archives of public administrations and the National Protestant Church, as well as from newspapers, these databases were used to study the transformation of a medium-sized European city, sociopolitical tensions embedded in demographic and social structures, and the impact of the immigrants who made the 'Calvinist Rome' a religiously mixed city.

LINKS stands for 'LINKing System for historical family reconstruction' and is a software system to link nominal data from the Dutch archives and ultimately reconstruct historical individuals and families. We present the background and philosophy of this matching system and explain its data structure and functioning. Currently the core data of the LINKS system consists of indexed civil certificates. These certificates are available from 1812 — the start of the Dutch Vital Registration — until the year they are confidential based on privacy laws. For more than 20 years, thousands of volunteers have been working to build this index, which contains not only the names of newborn, married and deceased persons, but also the names of their parents, places of birth, ages and sometimes their occupational titles. The software system LINKS includes the standardization of all input before linking, nominal record linkage procedures and identification of all unique persons involved in the system. All processes are repeatable and a strict distinction is maintained between source data, standardized, linked and enriched data and released data. Moreover, LINKS also informs archives about all kinds of errors and inconsistencies found during the cleaning and matching process. We will discuss two matching systems, the first is the original querying system that runs within a MySQL database environment and the second is a newly developed system, called burgerLinker, which is based on knowledge graphs and which is designed as a system that can be used independently from LINKS and is made available as open source software. Finally, we present the most important releases of LINKS data so far: two national releases that link birth and parental marriage certificates, creating families and pedigrees and an integrated dataset of persons, families and family trees in four provinces.

Over the last 60 years several major historical databases with reconstructed life courses of large populations have been launched. The development of these databases is indicative of considerable investments that have greatly expanded the possibilities for new research within the fields of history, demography, sociology, as well as other disciplines. In this volume spanning seven articles, eight databases are included that had a wide impact on research in various disciplines. Each database had its own unique genesis that is well described in the articles assembled in this volume. They inform readers about how these databases have changed the course of research in historical demography and related disciplines, how settled findings were challenged or confirmed, and how innovative investigations were launched and implemented. In the end we explore how research with this kind of databases will develop in future.