Evidence map›Paper›PMID 41235314›Full record

ArticleThe history of the family : an international quarterly2025

Identifying Matrilineal Kin Networks in the United States 1900-1940.

Matt A Nelson

Abstract read
In one paragraph

Article in The history of the family : an international quarterly, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Matt A NelsonSenior Research Scientist, Institute for Social Research and Data Innovation, University of Minnesota.ORCID 0000-0002-8849-4628

Funding

Microdata for Population Dynamics and Health ResearchR01HD043392 · NICHD · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Sarah M Flood, Steve Ruggles · 2002 to 2026
$14.8M
Multigenerational Longitudinal Panel for Research on AgingR01AG057679 · NIA · UNIVERSITY OF MINNESOTA · PI Julia AR Drew, Steve Ruggles · 2018 to 2026
$10.0M
Microdata for Analysis of Early Life Conditions, Health, and PopulationR01AG041831 · NIA · UNIVERSITY OF MINNESOTA · PI FITCH, CATHERINE A, RUGGLES, STEVE · 2012 to 2022
$5.9M
Minnesota Population Center Science and Technical CoreP2CHD041023 · NICHD · UNIVERSITY OF MINNESOTA · PI THERESA LOUISE OSYPUK · 2016 to 2026
$4.3M
NIA NIH HHS R01 AG041831NIA NIH HHS R01 AG057679NICHD NIH HHS P2C HD041023NICHD NIH HHS R01 HD043392
6 · The paper itself

Abstract

National-level analysis of historical women's life courses and kinship networks is understudied due to data limitations. Previous analysis of patrilineal kin propinquity in the United States relied on surnames to identify the probability of non-random isonymy (same surname) as a proxy for nearby kin. One limitation of this approach is losing matrilineal kinship networks due to women's changing surnames upon marriage. Using linked census data from IPUMS MLP, LIFE-M, and Census Tree for 1900-1940, this project aims to identify birth surnames for married women to better measure matrilineal kinship networks in the United States. Results using linked census suggest non-coresidential matrilineal kinship networks underwent a similar decline as proximate patrilineal kinship networks in this time period, but nuances suggest that we should not treat these declines similarly. Matrilineal and patrilineal kin propinquity differed in the life course patterns for currently married women, and accounting for both matrilineal and patrilineal kin propinquity are important to assess the full kinship network. The rates differ in some cases between the three linked datasets, suggesting that underlying biases in the data explain some of the differences. However, the trends are similar in all geographies and methods suggesting that the identified trends are not due to random chance. While this analysis does not directly identify kin, the data produced here allows other research to identify relations from other censuses with data quality flags indicating how relationships are determined. This marks a revolutionary improvement in national-level analyses for women's life course research in the early twentieth century.

Indexed as

censuskinshiplinked datawomen’s life course

Identifiers

PMID41235314
PMCPMC12610939

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.