Evidence map›Paper›PMID 34054338›Full record

ArticleDemographic research

Family status and women's career mobility during urban China's economic transition.

Guangye He, Xiaogang Wu

Open access · diamondAbstract read
In one paragraph

Article in Demographic research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
8.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 20 citations in OpenAlex.

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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

2 authors at 1 institution in 2 countries.

Guangye HeDepartment of Sociology, School of Social and Behavior Sciences, Nanjing University, Nanjing, China.
Xiaogang WuCenter for Applied Social and Economic Research, NYU Shanghai, Shanghai, China, and Department of Sociology, New York University, USA.
New York University Shanghai · CN

Funding

Sci-Tech Core-Population Dynamics Research CenterP2CHD044964 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI Xi Song · 2018 to 2026
$5.3M
NICHD NIH HHS P2C HD044964
6 · The paper itself

Abstract

backgroundIn contrast to the historical experience of Western welfare states, where social and family policies help create more integrated public-private spheres, marketization in China has presented a case of sphere separation. This phenomenon has important implications for the dynamics of gender inequality in economic transition.

objectiveThis article examines how family status is associated with women's career mobility in reform-era urban China and the impact of family on women's career choices across different reform stages.

methodBased on retrospective data from the Chinese General Social Survey (CGSS) in 2008, we adopt discrete-time logit models to examine the effects of marriage and childbearing on women's upward mobility, the risk of labor market exit, and how the effects vary over time.

resultsChinese women in the workforce are adversely affected by marriage and having dependent children. They are more likely than men to experience (involuntary, in particular) job exit to fulfill their roles as wives and mothers and less likely to move up in the career ladder. This pattern is more prominent as the economic reform proceeds.

conclusionMarketization has adversely affected Chinese women's career outcomes by increasing work-family tension after the work unit ( CONTRIBUTION: This study is one of the few empirical studies to attempt to explain the widening gender gap in China's job market from the perspective of family using the two-sphere separation framework. The framework originated in Western family studies but has been adapted to suit the context of urban China.

Identifiers

PMID34054338
PMCPMC8153691
OpenAlexW3127404437

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.