Lap Huynh
Biographic Data
| ID | 6204931 |
|---|---|
| NAME | Lap Huynh |
| GIVEN NAMES | Lap |
| FAMILY NAME | Huynh |
| SIGNATURE | HUYNH L |
| AFFILIATIONS | University of Minnesota |
| VERIFIED | No |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 44 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 2 |
Ipums full count datasets of enslaved persons and slaveholders in the United States in 1850 and 1860
Historical context and creation of the Ipums Ancestry full count population census data 1900–1930
IPUMS recently released final versions of full count census data for the United States 1900-1930. The information contained in these files is the product of three broad work stages: historical census enumeration, digitization, and IPUMS processing. The data were produced within an evolving institutional context and subjected to subsequent processes that had important ramifications on the final product. This paper documents these histories and pro…
New data sources for research on the nineteenth-century United States
IPUMS has finalized databases for each of the United States population censuses from 1850 to 1880. These data are the result of collaborations between FamilySearch and Ancestry.com, which provided the raw data, and IPUMS, which enhanced the data with editing, standardized coding, inter-census harmonization, and documentation. We discuss the data capture process conducted by the nineteenth-century United States Census Office, construction of the m…
Ipums full count datasets of the United States censuses of mortality, 1850–1880
This article describes four new IPUMS datasets constructed from the 1850, 1860, 1870, and 1880 Censuses of Mortality of the United States. We discuss the creation of the datasets, the variables included in each census year, and their potential for social science research. We highlight several limitations in the data and caution users about potential biases. Finally, we illustrate the usefulness of the new data by analyzing the relationship betwee…
The Effects of Standardizing Names for Record Linkage
Standardizing name strings before searching for links is common practice during record linkage and is generally believed to increase the size and quality of linked data sets. In this article, the authors quantify the impact of name standardization on historical record linkage, using data from nineteenth-century censuses of the United States and Norway as test cases
New Methods of Census Record Linking
The Minnesota Population Center (MPC) has released linked datasets through its NAPP and IPUMS projects, making them readily accessible to researchers. Prior to the availability of complete count census microdata from the MPC, researchers applied various forms of record-linking software. This essay describes the techniques used in the MPC's linking program and briefly compares this technique with those used by other researchers. The key feature of…
New Methods of Census Record Linking
The Minnesota Population Center (MPC) has released linked datasets through its NAPP and IPUMS projects, making them readily accessible to researchers. Prior to the availability of complete count census microdata from the MPC, researchers applied various forms of record-linking software. This essay describes the techniques used in the MPC's linking program and briefly compares this technique with those used by other researchers. The key feature of…
The Effects of Standardizing Names for Record Linkage
Standardizing name strings before searching for links is common practice during record linkage and is generally believed to increase the size and quality of linked data sets. In this article, the authors quantify the impact of name standardization on historical record linkage, using data from nineteenth-century censuses of the United States and Norway as test cases
New data sources for research on the nineteenth-century United States
IPUMS has finalized databases for each of the United States population censuses from 1850 to 1880. These data are the result of collaborations between FamilySearch and Ancestry.com, which provided the raw data, and IPUMS, which enhanced the data with editing, standardized coding, inter-census harmonization, and documentation. We discuss the data capture process conducted by the nineteenth-century United States Census Office, construction of the m…
Ipums full count datasets of enslaved persons and slaveholders in the United States in 1850 and 1860
Historical context and creation of the Ipums Ancestry full count population census data 1900–1930
IPUMS recently released final versions of full count census data for the United States 1900-1930. The information contained in these files is the product of three broad work stages: historical census enumeration, digitization, and IPUMS processing. The data were produced within an evolving institutional context and subjected to subsequent processes that had important ramifications on the final product. This paper documents these histories and pro…
Ipums full count datasets of the United States censuses of mortality, 1850–1880
This article describes four new IPUMS datasets constructed from the 1850, 1860, 1870, and 1880 Censuses of Mortality of the United States. We discuss the creation of the datasets, the variables included in each census year, and their potential for social science research. We highlight several limitations in the data and caution users about potential biases. Finally, we illustrate the usefulness of the new data by analyzing the relationship betwee…
The Effects of Standardizing Names for Record Linkage
Standardizing name strings before searching for links is common practice during record linkage and is generally believed to increase the size and quality of linked data sets. In this article, the authors quantify the impact of name standardization on historical record linkage, using data from nineteenth-century censuses of the United States and Norway as test cases
New Methods of Census Record Linking
The Minnesota Population Center (MPC) has released linked datasets through its NAPP and IPUMS projects, making them readily accessible to researchers. Prior to the availability of complete count census microdata from the MPC, researchers applied various forms of record-linking software. This essay describes the techniques used in the MPC's linking program and briefly compares this technique with those used by other researchers. The key feature of…
Ipums full count datasets of enslaved persons and slaveholders in the United States in 1850 and 1860
Historical context and creation of the Ipums Ancestry full count population census data 1900–1930
IPUMS recently released final versions of full count census data for the United States 1900-1930. The information contained in these files is the product of three broad work stages: historical census enumeration, digitization, and IPUMS processing. The data were produced within an evolving institutional context and subjected to subsequent processes that had important ramifications on the final product. This paper documents these histories and pro…
New data sources for research on the nineteenth-century United States
IPUMS has finalized databases for each of the United States population censuses from 1850 to 1880. These data are the result of collaborations between FamilySearch and Ancestry.com, which provided the raw data, and IPUMS, which enhanced the data with editing, standardized coding, inter-census harmonization, and documentation. We discuss the data capture process conducted by the nineteenth-century United States Census Office, construction of the m…
Ipums full count datasets of the United States censuses of mortality, 1850–1880
This article describes four new IPUMS datasets constructed from the 1850, 1860, 1870, and 1880 Censuses of Mortality of the United States. We discuss the creation of the datasets, the variables included in each census year, and their potential for social science research. We highlight several limitations in the data and caution users about potential biases. Finally, we illustrate the usefulness of the new data by analyzing the relationship betwee…
Demography (5 works) · Demography (5 works) · Computer Science (4 works) · Sociology (4 works) · Census (3 works) · Genealogy (3 works) · Geography (3 works) · History (3 works) · History (3 works) · Population (3 works)