The Ural Population Project (URAPP) is built from individual level data transcriptions of 19th- to early 20th-century parish records and mid-19th-century census-like tax revisions manuscripts. This article discusses the source material, the contents, the history of creation and the strategy of the URAPP database and the outcome of the main research topics so far, including historical demography, Jewish studies, indigenous studies and studies of religious minorities in the Urals and Siberia. Our studies of the ethno-religious cultural landscape of the Urals and northwestern Siberia as well as participation in population history projects was more vital backgrounds than the traditional focus on aggregates. The over 65,000 vital events transcribed from parish records of Russian Orthodox Churches and minority religions in and around Ekaterinburg have been the basis for studies of mortality, nuptiality, religion and other characteristics. We found that the Jewish population kept their traditions and connections with relatives in the Pale of Settlement. Prisoners of WWI usually marrying within their own religious group. Infant mortality in Ekaterinburg was lower among Jews and the Catholics, minorities with higher education and western background, while the Orthodox majority exposed their newborn to extremely tough baptism. The burial records show cases of the Spanish flu in 1918–1919, but on a lower level than in the West, supporting recent theories that estimates of flu mortality may be too high. Based on the tax revisions, polygyny was officially recognized among the indigenous Siberian people. The strategy of the URAPP project has evolved from transcribing microdata about minorities towards covering the whole population.
{"title":"The Ural Population Project. Demography and Culture From Microdata in a European-Asian Border Region","authors":"E. Glavatskaya, Julia Borovik, G. Thorvaldsen","doi":"10.51964/hlcs12320","DOIUrl":"https://doi.org/10.51964/hlcs12320","url":null,"abstract":"The Ural Population Project (URAPP) is built from individual level data transcriptions of 19th- to early 20th-century parish records and mid-19th-century census-like tax revisions manuscripts. This article discusses the source material, the contents, the history of creation and the strategy of the URAPP database and the outcome of the main research topics so far, including historical demography, Jewish studies, indigenous studies and studies of religious minorities in the Urals and Siberia. Our studies of the ethno-religious cultural landscape of the Urals and northwestern Siberia as well as participation in population history projects was more vital backgrounds than the traditional focus on aggregates. The over 65,000 vital events transcribed from parish records of Russian Orthodox Churches and minority religions in and around Ekaterinburg have been the basis for studies of mortality, nuptiality, religion and other characteristics. We found that the Jewish population kept their traditions and connections with relatives in the Pale of Settlement. Prisoners of WWI usually marrying within their own religious group. Infant mortality in Ekaterinburg was lower among Jews and the Catholics, minorities with higher education and western background, while the Orthodox majority exposed their newborn to extremely tough baptism. The burial records show cases of the Spanish flu in 1918–1919, but on a lower level than in the West, supporting recent theories that estimates of flu mortality may be too high. Based on the tax revisions, polygyny was officially recognized among the indigenous Siberian people. The strategy of the URAPP project has evolved from transcribing microdata about minorities towards covering the whole population.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44593302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luminița Dumănescu, M. Hărăguș, Angela Lumezeanu, E. Holom, Nicoleta Hegedűs, Daniela Mârza, D. Covaci, Ioan Bolovan
The Historical Population Database of Transylvania (HPDT) is a research tool for population studies developed since 2014 at the Centre for Population Studies in Cluj-Napoca, financed by an SEE-Norway Grant. HPDT employs a source-oriented approach for recording data from the parish registers kept by the Transylvanian churches, focusing primarily on the main vital events such as births, marriages, and deaths. The data entry process was followed by the standardization of various information, such as names, occupations, locations and causes of death, thus allowing the initiation of a linkage process. The database has already been employed in a wide-ranging series of analyses conducted on datasets extracted from HPDT, which include infant and adult mortality, nuptiality and age at first marriage, social mobility, and the medicalization of childbirth. The wealth of information it includes will enable many more scientific investigations.
{"title":"Historical Population Database of Transylvania. Sources, Particularities, Challenges, and Early Findings","authors":"Luminița Dumănescu, M. Hărăguș, Angela Lumezeanu, E. Holom, Nicoleta Hegedűs, Daniela Mârza, D. Covaci, Ioan Bolovan","doi":"10.51964/hlcs12038","DOIUrl":"https://doi.org/10.51964/hlcs12038","url":null,"abstract":"The Historical Population Database of Transylvania (HPDT) is a research tool for population studies developed since 2014 at the Centre for Population Studies in Cluj-Napoca, financed by an SEE-Norway Grant. HPDT employs a source-oriented approach for recording data from the parish registers kept by the Transylvanian churches, focusing primarily on the main vital events such as births, marriages, and deaths. The data entry process was followed by the standardization of various information, such as names, occupations, locations and causes of death, thus allowing the initiation of a linkage process. The database has already been employed in a wide-ranging series of analyses conducted on datasets extracted from HPDT, which include infant and adult mortality, nuptiality and age at first marriage, social mobility, and the medicalization of childbirth. The wealth of information it includes will enable many more scientific investigations.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48508376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Pujadas-Mora, A. Fornés, Oriol Ramos Terrades, J. Lladós, Jialuo Chen, M. Valls-Fígols, A. Cabré
The Barcelona Historical Marriage Database (BHMD) gathers records of the more than 600,000 marriages celebrated in the Diocese of Barcelona and their taxation registered in Barcelona Cathedral's so-called Marriage Licenses Books for the long period 1451–1905 and the BALL Demographic Database brings together the individual information recorded in the population registers, censuses and fiscal censuses of the main municipalities of the county of Baix Llobregat (Barcelona). In this ongoing collection 263,786 individual observations have been assembled, dating from the period between 1828 and 1965 by December 2020. The two databases started as part of different interdisciplinary research projects at the crossroads of Historical Demography and Computer Vision. Their construction uses artificial intelligence and computer vision methods as Handwriting Recognition to reduce the time of execution. However, its current state still requires some human intervention which explains the implemented crowdsourcing and game sourcing experiences. Moreover, knowledge graph techniques have allowed the application of advanced record linkage to link the same individuals and families across time and space. Moreover, we will discuss the main research lines using both databases developed so far in historical demography.
{"title":"The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomic Data","authors":"J. Pujadas-Mora, A. Fornés, Oriol Ramos Terrades, J. Lladós, Jialuo Chen, M. Valls-Fígols, A. Cabré","doi":"10.51964/hlcs11971","DOIUrl":"https://doi.org/10.51964/hlcs11971","url":null,"abstract":"The Barcelona Historical Marriage Database (BHMD) gathers records of the more than 600,000 marriages celebrated in the Diocese of Barcelona and their taxation registered in Barcelona Cathedral's so-called Marriage Licenses Books for the long period 1451–1905 and the BALL Demographic Database brings together the individual information recorded in the population registers, censuses and fiscal censuses of the main municipalities of the county of Baix Llobregat (Barcelona). In this ongoing collection 263,786 individual observations have been assembled, dating from the period between 1828 and 1965 by December 2020. The two databases started as part of different interdisciplinary research projects at the crossroads of Historical Demography and Computer Vision. Their construction uses artificial intelligence and computer vision methods as Handwriting Recognition to reduce the time of execution. However, its current state still requires some human intervention which explains the implemented crowdsourcing and game sourcing experiences. Moreover, knowledge graph techniques have allowed the application of advanced record linkage to link the same individuals and families across time and space. Moreover, we will discuss the main research lines using both databases developed so far in historical demography.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47190781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Groningen Integral History project launched in 1987 aimed to sketch the lives of people from various social classes in the Dutch province of Groningen in the 19th and early 20th century. One part was the creation of the Groningen Integral History Cohort Database (GIHCD), reconstructing complete individual life courses of 5,280 persons (RPs) born between 1811 and 1872. The quality of the database has become very high by now, despite the lengthy and difficult process of shaping it over 35 years. More than 98% of the RPs (and for some parts of the database even more than 99%) could be followed until their death or until a migration abroad. Even for the life courses of those moving abroad information is available for most RPs. In this article, we primarily focus on the rural part of the database (n = 4,320), the quality of which is the highest and has had the most significant tangible research impact. Building on information from the Dutch civil registration system (from 1811) and the population registers (from 1850), the database includes multiple individual-level variables. In the technical part of the article, we provide an extensive overview of the available variables and summarize the transformation of the rural part of the database into an Intermediate Data Structure (IDS). Since the early 1990s, historians from the University of Groningen have used GIHCD in quite some publications. At the end of this article, we provide a summary of the main outcomes of these publications.
{"title":"The Groningen Integral History Cohort Database. Development, Design and Output","authors":"R. Paping, Dinos Sevdalakis","doi":"10.51964/hlcs12033","DOIUrl":"https://doi.org/10.51964/hlcs12033","url":null,"abstract":"The Groningen Integral History project launched in 1987 aimed to sketch the lives of people from various social classes in the Dutch province of Groningen in the 19th and early 20th century. One part was the creation of the Groningen Integral History Cohort Database (GIHCD), reconstructing complete individual life courses of 5,280 persons (RPs) born between 1811 and 1872. The quality of the database has become very high by now, despite the lengthy and difficult process of shaping it over 35 years. More than 98% of the RPs (and for some parts of the database even more than 99%) could be followed until their death or until a migration abroad. Even for the life courses of those moving abroad information is available for most RPs. In this article, we primarily focus on the rural part of the database (n = 4,320), the quality of which is the highest and has had the most significant tangible research impact. Building on information from the Dutch civil registration system (from 1811) and the population registers (from 1850), the database includes multiple individual-level variables. In the technical part of the article, we provide an extensive overview of the available variables and summarize the transformation of the rural part of the database into an Intermediate Data Structure (IDS). Since the early 1990s, historians from the University of Groningen have used GIHCD in quite some publications. At the end of this article, we provide a summary of the main outcomes of these publications.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46050500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ken R. Smith, A. Fraser, Diana Lane Reed, Jahn B. Barlow, H. Hanson, J. West, S. Knight, Navina Forsythe, G. Mineau
Improving our understanding of the socio-environmental and genetic bases of disease and health outcomes among individuals, families, and populations over time requires extensive longitudinal data on multiple attributes for entire communities, states or nations. This requirement can be difficult to achieve. In this paper we describe a successful example of a database that meets these needs. The Utah Population Database (UPDB) is a unique and powerful database rarely found in the world that has been addressing these data requirements for over 40 years. The UPDB at the University of Utah is one of the world’s richest sources of in-depth information that supports research on genetics, epidemiology, demography, history, and public health. Genetic researchers have used UPDB to identify and study individuals and families that have higher than normal incidence of diseases or other traits, to analyze patterns of genetic inheritance, and to identify specific genetic mutations. Demographers and other social scientists are increasingly using the UPDB to study issues such as trends in fertility transitions and shifts in mortality patterns for both infants and adults. A central component of the UPDB is an extensive set of Utah family histories, in which family members are linked to demographic and medical information. The UPDB includes medical information about cancer, causes of death, and medical details associated with births. It also includes diagnostic records from statewide insurance claims data and healthcare facilities (hospital discharge, ambulatory surgery, emergency department encounters). UPDB is also linked to Medicare claims data, a federal health insurance program generally for persons age 65 or older. The UPDB provides access to information on more than 11 million individuals and supports nearly 400 research projects. We describe in detail the data components of the UPDB, how it can be accessed, issues related to its development, record linkage, governance and privacy protections, as well as plans for future developments.
{"title":"The Utah Population Database. A Model for Linking Medical and Genealogical Records for Population Health Research","authors":"Ken R. Smith, A. Fraser, Diana Lane Reed, Jahn B. Barlow, H. Hanson, J. West, S. Knight, Navina Forsythe, G. Mineau","doi":"10.51964/hlcs11681","DOIUrl":"https://doi.org/10.51964/hlcs11681","url":null,"abstract":"Improving our understanding of the socio-environmental and genetic bases of disease and health outcomes among individuals, families, and populations over time requires extensive longitudinal data on multiple attributes for entire communities, states or nations. This requirement can be difficult to achieve. In this paper we describe a successful example of a database that meets these needs. The Utah Population Database (UPDB) is a unique and powerful database rarely found in the world that has been addressing these data requirements for over 40 years. The UPDB at the University of Utah is one of the world’s richest sources of in-depth information that supports research on genetics, epidemiology, demography, history, and public health. Genetic researchers have used UPDB to identify and study individuals and families that have higher than normal incidence of diseases or other traits, to analyze patterns of genetic inheritance, and to identify specific genetic mutations. Demographers and other social scientists are increasingly using the UPDB to study issues such as trends in fertility transitions and shifts in mortality patterns for both infants and adults. A central component of the UPDB is an extensive set of Utah family histories, in which family members are linked to demographic and medical information. The UPDB includes medical information about cancer, causes of death, and medical details associated with births. It also includes diagnostic records from statewide insurance claims data and healthcare facilities (hospital discharge, ambulatory surgery, emergency department encounters). UPDB is also linked to Medicare claims data, a federal health insurance program generally for persons age 65 or older. The UPDB provides access to information on more than 11 million individuals and supports nearly 400 research projects. We describe in detail the data components of the UPDB, how it can be accessed, issues related to its development, record linkage, governance and privacy protections, as well as plans for future developments.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49470471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we share the experience of collecting and organizing pre-modern Korean historical materials into a searchable digital archive. The Ajou Interdisciplinary Research Group (AIRG) has continuously collected historical data of pre-modern Korea for the past 10 years to assist the study of family history, historical demographics, and social mobility. This paper describes the rich data sources for historical studies of Korea, such as household registers, genealogies, and state examination registers, and we summarize contributions to the study of historical demography and related fields.
{"title":"Building an Archival Database for Visualizing Historical Networks. A Case for Pre-Modern Korea","authors":"Seung-youn Paek, Jong Hee Park, Sangkuk Lee","doi":"10.51964/hlcs11718","DOIUrl":"https://doi.org/10.51964/hlcs11718","url":null,"abstract":"In this paper, we share the experience of collecting and organizing pre-modern Korean historical materials into a searchable digital archive. The Ajou Interdisciplinary Research Group (AIRG) has continuously collected historical data of pre-modern Korea for the past 10 years to assist the study of family history, historical demographics, and social mobility. This paper describes the rich data sources for historical studies of Korea, such as household registers, genealogies, and state examination registers, and we summarize contributions to the study of historical demography and related fields.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46424665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The establishment of the Norwegian Historical Data Centre, the 1801 project at the University of Bergen and the data transcriptions and scanned versions of the sources in the National Archives made Norwegian microdata much more available. A more detailed description of the digital techniques applied to the wealth of censuses, church records and other types of nominative data from the 18th century onwards, will be presented in a separate article. Our main focus here is to summarize the impact of the research that has been produced based on the Norwegian historical microdata. These studies span a wide range of fields within social history and historical demography: Emigration, immigration, internal migration, fertility, nuptiality, family history and last but not least mortality studies with a priority given to infant mortality. A recent development is the building of a national historical population register covering the 19th and 20th centuries.
{"title":"The Impact of Microdata in Norwegian Historiography 1970 to 2020","authors":"H. Sommerseth, G. Thorvaldsen","doi":"10.51964/hlcs11675","DOIUrl":"https://doi.org/10.51964/hlcs11675","url":null,"abstract":"The establishment of the Norwegian Historical Data Centre, the 1801 project at the University of Bergen and the data transcriptions and scanned versions of the sources in the National Archives made Norwegian microdata much more available. A more detailed description of the digital techniques applied to the wealth of censuses, church records and other types of nominative data from the 18th century onwards, will be presented in a separate article. Our main focus here is to summarize the impact of the research that has been produced based on the Norwegian historical microdata. These studies span a wide range of fields within social history and historical demography: Emigration, immigration, internal migration, fertility, nuptiality, family history and last but not least mortality studies with a priority given to infant mortality. A recent development is the building of a national historical population register covering the 19th and 20th centuries.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42045061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article introduces the Xavier database, one of the major sources for studying historical populations in Japan. The database consists of 162 years of annual observations for 28,105 individuals living in three villages and one town of the current Fukushima prefecture between 1708 and 1870. We review the extensive efforts of the founder of Japanese historical demography, Akira Hayami, and his group in collecting, transcribing, coding, and finally making local population registers into this database for demographic analysis. We discuss the studies that flourished domestically and internationally using the data in the last two decades, followed by the discussion of current and promising development.
{"title":"Thank You, Akira Hayami! The Xavier Database of Historical Japan","authors":"S. Kurosu, Miyuki Takahashi, Hao Dong","doi":"10.51964/hlcs11113","DOIUrl":"https://doi.org/10.51964/hlcs11113","url":null,"abstract":"This article introduces the Xavier database, one of the major sources for studying historical populations in Japan. The database consists of 162 years of annual observations for 28,105 individuals living in three villages and one town of the current Fukushima prefecture between 1708 and 1870. We review the extensive efforts of the founder of Japanese historical demography, Akira Hayami, and his group in collecting, transcribing, coding, and finally making local population registers into this database for demographic analysis. We discuss the studies that flourished domestically and internationally using the data in the last two decades, followed by the discussion of current and promising development.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45889107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Very little is known about what family life looked like for settlers in colonial South Africa during the 18th or 19th century, nor how events over these centuries might have affected demographic change. The primary reason for this lacuna is a shortage of adequate data. Historians and genealogists have, over the last century, worked to combine the rich administrative records that are available in the Cape Archives in Cape Town and beyond, into a single genealogical volume of all settlers living in the 18th, 19th and early 20th century. Until recently, this valuable resource was not in a format that would enable its use for the type of event-history analyses that have come to dominate the field of contemporary historical demography. This is now changing with the introduction of the South African Families database (SAF). SAF is one of very few databases known to document a full population of immigrants and their families over several generations. This article introduces provides a brief background to, and technical overview of, the construction of the SAF. It discusses both the merits and limitations of its use in longitudinal demographic studies and offers a look into the types of studies it can enable.
{"title":"The South African Families Database","authors":"Jeanne Cilliers","doi":"10.51964/hlcs11095","DOIUrl":"https://doi.org/10.51964/hlcs11095","url":null,"abstract":"Very little is known about what family life looked like for settlers in colonial South Africa during the 18th or 19th century, nor how events over these centuries might have affected demographic change. The primary reason for this lacuna is a shortage of adequate data. Historians and genealogists have, over the last century, worked to combine the rich administrative records that are available in the Cape Archives in Cape Town and beyond, into a single genealogical volume of all settlers living in the 18th, 19th and early 20th century. Until recently, this valuable resource was not in a format that would enable its use for the type of event-history analyses that have come to dominate the field of contemporary historical demography. This is now changing with the introduction of the South African Families database (SAF). SAF is one of very few databases known to document a full population of immigrants and their families over several generations. This article introduces provides a brief background to, and technical overview of, the construction of the SAF. It discusses both the merits and limitations of its use in longitudinal demographic studies and offers a look into the types of studies it can enable.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49446093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Scanian Economic-Demographic Database (SEDD) at the Centre for Economic Demography (CED), Lund University was built to answer questions derived from previous research using macro data from 1749 onwards. It includes longitudinal micro data for a regional sample of rural, semi-urban, and urban parishes in southern Sweden from 1646 to 1968 for approximately 175,000 individuals. In addition to the data on births, deaths, marriages, and occupations, it includes data on migration, household size, landholdings, taxation, and heights from the 1800s onwards and on income from 1865 onwards. After being linked from 1968 to 2015 to a range of national registers with detailed demographic and socioeconomic information, it includes 825,000 individuals. The richness and wide range of micro data have allowed researchers to follow individuals throughout their lives and across generations, covering extensive periods, and to make comparisons with results from macro data. This research has partly confirmed the established view on long-term changes in living standards and demographics in Sweden but has also brought into question some previously held truths.
{"title":"The Long Road to Health and Prosperity, Southern Sweden, 1765-2015. Research Contributions From the Scanian Economic-Demographic Database (SEDD)","authors":"T. Bengtsson, M. Dribe","doi":"10.51964/hlcs10941","DOIUrl":"https://doi.org/10.51964/hlcs10941","url":null,"abstract":"The Scanian Economic-Demographic Database (SEDD) at the Centre for Economic Demography (CED), Lund University was built to answer questions derived from previous research using macro data from 1749 onwards. It includes longitudinal micro data for a regional sample of rural, semi-urban, and urban parishes in southern Sweden from 1646 to 1968 for approximately 175,000 individuals. In addition to the data on births, deaths, marriages, and occupations, it includes data on migration, household size, landholdings, taxation, and heights from the 1800s onwards and on income from 1865 onwards. After being linked from 1968 to 2015 to a range of national registers with detailed demographic and socioeconomic information, it includes 825,000 individuals. The richness and wide range of micro data have allowed researchers to follow individuals throughout their lives and across generations, covering extensive periods, and to make comparisons with results from macro data. This research has partly confirmed the established view on long-term changes in living standards and demographics in Sweden but has also brought into question some previously held truths.","PeriodicalId":73242,"journal":{"name":"Historical life course studies","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43958606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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