https://hlcs.nl/issue/feedHistorical Life Course Studies2023-07-10T13:00:12+02:00Marja Kosterehps-journal@iisg.nlOpen Journal Systems<p><em>Historical Life Course Studies</em> is the electronic journal of the European Historical Population Samples Network (EHPS-Net) and is published by the International Institute of Social History (IISH). The journal is the primary publishing outlet for research involved in the conversion of existing European and non-European large historical demographic databases into a common format, the Intermediate Data Structure, and for studies based on these databases. The journal publishes both methodological and substantive research articles.</p>https://hlcs.nl/article/view/12920Collaborations Between IPUMS and Genealogical Organizations, 1999-20222022-09-26T21:36:15+02:00Steven Rugglesruggles@umn.edu<p>From 1999 to 2019, IPUMS collaborated with genealogical organizations to develop massive individual-level census datasets spanning the 1790 through 1940 period, and we are currently working on the 1950 census. This research note describes how our genealogical collaborations came about. We focus on our collaborations with the Church of Jesus Christ of Latter-Day Saints Family and Church History Department (later known as FamilySearch) and the private genealogical companies HeritageQuest and Ancestry.com.</p>2023-01-05T00:00:00+01:00Copyright (c) 2023 Steven Ruggleshttps://hlcs.nl/article/view/12032Cause-Specific Infant Mortality in Copenhagen 1861–1911 Explored Using Individual-Level Data2022-06-06T10:43:27+02:00Louise Ludvigsenlouise.ludvigsen@hum.ku.dkBarbara Revuelta-Eugerciosbre@sa.dkAnne Løkkeal@hum.ku.dk<p>This study explores cause-specific infant mortality in Copenhagen between 1861 and 1911, using newly available individual-level data from The Copenhagen Burial Register, as part of a larger comparative project within the SHiP network (Studying the history of Health in Port Cities). The aim is to determine the dominant cause of death patterns for infants and to explore how the ICD10h coding system performs with the Danish individual level-historical causes of death. The results show that in Copenhagen, infant mortality began a distinct decline during the period of study (1861–1911), but the city experienced only very few changes in the cause of death pattern. While a transition from symptomatic to more specific causes of death took place over time, the largest killers overall were the water-food borne and airborne diseases, with a respectively summer and winter peak. The airborne and water-food borne diseases were mainly dominant amongst the post-neonates, whose mortality made up an increasingly larger share of infant deaths. Finally, the results show that although coding the Danish causes of death to the ICD10h has proven successful, more attention needs to be paid to different uses of the same cause of death by different nations, such as the case of atrophy.</p>2023-01-17T00:00:00+01:00Copyright (c) 2023 Louise Ludvigsen, Barbara Revuelta-Eugercios, Anne Løkkehttps://hlcs.nl/article/view/13565Construction of the Finnish Army in World War II Database2023-01-10T11:29:32+01:00Ilari Taskinenilari.taskinen@tuni.fi<p>This article introduces the Finnish Army in World War II Database (FA2W) currently under construction that is being built to study the effects of World War II on Finnish society. The database is a stratified sample of 4,253 representative of the men who served in the Finnish Army in World War II. The data have been gathered from the military service record collection of the Finnish Army, which holds files on practically all draft-age Finnish men of the birth cohort 1903–1926 and around 70% of the birth cohorts 1897–1902. The amount of data is extensive, containing over 60 different variables. The main part of the database consists of men's military careers, comprising longitudinal data on their positions in society and in the army (e.g., civilian/conscript/frontline service), military unit, military branch, task, rank, and service class. Other information includes socio-economic information from the draft and wartime and war experiences, such as wounds, illnesses, medical treatments, death, and honors. In the future the database will be expanded with men’s postwar life trajectories to study the long-term effects of the war.</p>2023-01-23T00:00:00+01:00Copyright (c) 2023 Ilari Taskinenhttps://hlcs.nl/article/view/12290What was Killing Babies in Trondheim? An Investigation of Infant Mortality Using Individual Level Cause of Death Data, 1830–19072022-07-07T21:55:06+02:00Hilde Leikny Sommersethhilde.sommerseth@uit.no<p>This paper examines infant mortality amongst newborns in Trondheim city, 1830–1907, working specifically with individual level cause of death data. Findings show that infant mortality in the city started to drop from 1895, primarily as a result of a decline in post-neonatal mortality. At the start of the decline air-borne diseases accounted for nearly half of the deaths, and water-food borne for around one third. The drop was predominantly driven by a decline in these two causal groups, and seasonal fluctuations became less pronounced. Because of the fall in post-neonatal mortality, the relative risk of dying amongst neonates rose towards the end of the period. Although 'convulsions' accounted for 50–70% of all infant deaths between 1830 and 1860, this cause had faded away to near insignificance by the beginning of the 1900s. Here we aim to assess the extent to which this particular aspect of decline can be explained by alterations to official instructions regarding registration and in registration practice itself. This article proposes that the decline in deaths from 'convulsions' can be explained by a relabelling of such deaths into 'congenital and birth disorders' amongst neonates, and a mix of 'water-food borne' and 'air-borne diseases' amongst post-neonates. This argument is supported by the fact that the timing of the decline corresponds with the introduction of cause of death certificates issued by medical practitioners, and which most likely resulted in fewer causes of death being reported by lay informants who could only offer vague symptoms rather than informed diagnoses.</p>2023-03-02T00:00:00+01:00Copyright (c) 2023 Hilde L. Sommersethhttps://hlcs.nl/article/view/12163The Demographic Database — History of Technical and Methodological Achievements2022-06-01T13:51:40+02:00Pär Vikströmpar.vikstrom@umu.seMaria Larssonmaria.larsson@umu.seElisabeth Engbergelisabeth.engberg@umu.seSören Edvinssonsoren.edvinsson@umu.se<p>The Demographic Data Base (DDB) at the Centre for Demographic and Ageing Research (CEDAR) at Umeå University has since the 1970s been building longitudinal population databases and disseminating data for research. The databases were built to serve as national research infrastructures, useful for addressing an indefinite number of research questions within a broad range of scientific fields, and open to all academic researchers who wanted to use the data. A countless number of customized datasets have been prepared and distributed to researchers in Sweden and abroad and to date, the research has resulted in more than a thousand published scientific reports, books, and articles within a broad range of academic fields. This article will focus on the development of techniques and methods used to store and structure the data at DDB from the beginning in 1973 until today. This includes digitization methods, database design and methods for linkage. The different systems developed for implementing these methods are also described and to some extent, the hardware used.</p>2023-03-30T00:00:00+02:00Copyright (c) 2023 Pär Vikström, Maria Larsson, Elisabeth Engberg, Sören Edvinssonhttps://hlcs.nl/article/view/13984PRDH and IMPQ 1800–1849 Quebec Historical Family Reconstitution. Content, Design and Biographical Completeness2023-04-03T10:12:05+02:00Lisa Dillonly.dillon@umontreal.caMarilyn Amorevieta-Gentilmarilyn.amorevieta@umontreal.caAlain Gagnonalain.gagnon.4@umontreal.caBertrand Desjardinsbertrand.desjardins@umontreal.ca<p>Since 1966, the Programme de recherche en démographie historique (PRDH) has worked to create comprehensive genealogical data of the Quebec population. The PRDH longitudinal database, the Registre de la population du Québec ancien (RPQA), draws upon the French Catholic parish registers of the St. Lawrence Valley as its main source material. This family reconstitution covers the French Catholic population of Quebec up to 1799, along with deaths after 1800 of persons born before 1750. Subsequent partnerships with l’Institut Généalogique Drouin, FamilySearch and Ancestry as well as collaboration on the 2011–2017 Infrastructure intégrée des microdonnées historiques de la population du Québec (1621–1965) (IMPQ) project enabled the PRDH to continue efforts to reconstitute the French Catholic population up to 1849. Despite these advances, pushing family reconstitution forward to the mid-19th century has forced the PRDH team to reckon with the increasingly mixed and geographically mobile Quebec population of the 19th and early 20th centuries. This article describes the content and design of the RPQA database, detailing the structure of the RPQA relational database and the breadth of variables available for data management and analysis. It then describes features of the IMPQ extension of family reconstitution from 1800 to 1849, including observational protocols necessary to use these data and consideration of data completeness after 1800. At the same time, the article addresses the fundamental question, "what is my population?" as part of a broader reflection upon the target population encompassed by these data.</p>2023-04-25T00:00:00+02:00Copyright (c) 2023 Lisa Dillon, Marilyn Amorevieta-Gentil, Alain Gagnon, Bertrand Desjardinshttps://hlcs.nl/article/view/14315The Development of Microhistorical Databases in Norway. A Historiography2023-05-04T13:14:45+02:00Gunnar Thorvaldsengunnar.thorvaldsen@uit.noLars Holdenlars.holden@nr.no<p>Norwegian work on microdata started out with the full count 1801 census and census and vital records from around the capital. Today, most census and ministerial records from 1801 until the mid-20th century have been scanned, transcriptions are being completed, much is encoded and made available via the websites of the Digital National Archives and UiT The Arctic University of Norway. This article complements a previous publication on empirical results from historical microdata. It is primarily organized by technical issues: digitization of source materials, encoding and standardization, building of the Historical Population Register for the period since 1800, record linkage and source criticism as well as GIS. Presently, partner institutions are building the Historical Population Register with prolonged support from the Norwegian Research Council. This will contain longitudinal records of the nine million persons who lived in Norway since 1800. The register increasingly makes it possible to follow the entire population. Unique personal IDs with corresponding URLs to the person page providing links to many sources introduce a new level of historical documentation. Cross-sectional and vital records are being interlinked with automatic and manual record linkage software. Longitudinal data is available for searching as timelines and in Intermediate Data Structure format from UiT The Arctic University and for searching at Histreg.no, which also caters for manual editing. We are well on the way to creating a database that can fill the void in the two centuries before the Central Population Register starts in 1964.</p>2023-05-11T00:00:00+02:00Copyright (c) 2023 Gunnar Thorvaldsen, Lars Holdenhttps://hlcs.nl/article/view/14685LINKS. A System for Historical Family Reconstruction in the Netherlands2023-05-22T09:44:14+02:00Kees Mandemakerskma@iigs.nlGerrit Bloothooftg.bloothooft@uu.nlFons Laanfons.laan@xs4all.nlJoe Raadjoe.raad@universite-paris-saclay.frRick J. Mouritsrick.mourits@iisg.nlRichard L. Zijdemanrichard.zijdeman@iisg.nl<p>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.</p>2023-06-01T00:00:00+02:00Copyright (c) 2023 Kees Mandemakers, Gerrit Bloothooft, Fons Laan, Joe Raad, Rick J. Mourits, Richard L. Zijdemanhttps://hlcs.nl/article/view/14840Introduction: Major Databases with Historical Longitudinal Population Data: Development, Impact and Results2023-05-25T17:15:57+02:00Sören Edvinssonsoren.edvinsson@umu.seKees Mandemakerskma@iigs.nlKen R. Smithken.smith@fcs.utah.edu<p>Over the last 60 years several major historical databases with reconstructed life courses of large populations spanning decades 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 have 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.</p>2023-05-30T00:00:00+02:00Copyright (c) 2023 Sören Edvinsson, Kees Mandemakers, Ken R. Smithhttps://hlcs.nl/article/view/15619Slavery in Suriname. A Reconstruction of Life Courses, 1830–18632023-07-03T09:16:17+02:00Coen W. van Galencoen.vangalen@ru.nlRick J. Mouritsrick.mourits@iisg.nlMatthias Rosenbaum-Feldbrüggematthias.rosenbaum-feldbruegge@ru.nlMaartje A.B.maartje.ab@ru.nlJasmijn Janssenjasmijn.janssen@ru.nlBjörn Quanjerbjorn.quanjer@ru.nlThunnis van Oortthunnis.vanoort@ru.nlJan Kokjan.kok@ru.nl<p>The <em>slavenregisters </em>or slave registers of Suriname offer a unique perspective on the social and demographic history of a people in bondage. Thanks to a citizen science project, the archival sources were transcribed in 2017 by hundreds of volunteers. The transcriptions were used to create a longitudinal database of more than 90,000 enslaved persons. This paper describes the sources, data entry, and cleaning to create a standardized database as well as the matching needed to construct life courses. We discuss the best practices we have learned along the way. Finally, it offers prospects for research and expansion of the database to other population sources and areas.</p>2023-07-06T00:00:00+02:00Copyright (c) 2023 Coen W. van Galen, Rick J. Mourits, Matthias Rosenbaum-Feldbrügge, Maartje A.B., Jasmijn Janssen, Björn Quanjer, Thunnis van Oort, Jan Kokhttps://hlcs.nl/article/view/15621Geneva. An Urban Sociodemographic Database2023-07-03T11:06:59+02:00Michel Orismichel.oris@unige.chOlivier Perrouxolix72@outlook.frGrazyna Ryczkowskagrazyna@montmollin.netReto Schumacherreto.schumacher@vd.chAdrien Remunda.p.p.remund@rug.nlGilbert RitschardGilbert.Ritschard@unige.ch<p>The Geneva databases are a data resource covering the period 1800<span style="color: #4d5156; font-family: arial, sans-serif; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: #ffffff; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; display: inline !important; float: none;">–</span>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<span style="color: #4d5156; font-family: arial, sans-serif; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: #ffffff; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; display: inline !important; float: none;">–</span>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.</p>2023-07-11T00:00:00+02:00Copyright (c) 2023 Michel Oris, Olivier Perroux, Grazyna Ryczkowska, Reto Schumacher, Adrien Remund, Gilbert Ritschardhttps://hlcs.nl/article/view/15759Introduction: Content, Design and Structure of Major Databases with Historical Longitudinal Population Data2023-07-10T13:00:12+02:00George Alteraltergc@umich.eduKees Mandemakerskma@iigs.nlHélène VézinaHelene_Vezina@uqac.ca<p>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.</p>2023-07-17T00:00:00+02:00Copyright (c) 2023 George Alter, Kees Mandemakers, Vézina H`élènehttps://hlcs.nl/article/view/13438What was Killing Babies in Amsterdam? A Study of Infant Mortality Patterns Using Individual-Level Cause of Death Data, 1856–19042023-03-13T10:44:40+01:00Angélique Janssensangelique.janssens@ru.nlTim Riswicktim.riswick@ru.nl<p>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.</p>2023-08-21T00:00:00+02:00Copyright (c) 2023 Angélique Janssens, Tim Riswickhttps://hlcs.nl/article/view/13510Genetic and Shared-Environment Effects on Stature and Lifespan. A Study of Dutch Birth Cohorts (1785–1920) Based on Genealogies2023-02-03T10:49:59+01:00Jan Kokjan.kok@ru.nl<p>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.</p>2023-08-28T00:00:00+02:00Copyright (c) 2023 Jan Kok