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Cited by 174

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

Daily variation in ethnic identity, ethnic behaviors, and psychological well-being among American adolescents of Chinese Descent

Yip, Tiffany, Fuligni, Andrew J·2002·Child Development
DOI 10.1111/1467-8624.00490
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Abstract

This study examined the links among Chinese American adolescents’ (N= 96) global ethnic identity and their ethnic behaviors, ethnic identity salience, and psychological well–being based on daily diaries collected over a 2–week period. The daily association between engagement in ethnic behaviors and ethnic salience was positive regardless of overall ethnic identity. The daily–level association between ethnic identity salience and well–being, however, was dependent on adolescents’ global ethnic identity. Among adolescents who were moderate or high in global ethnic identity, ethnic identity salience was consistently associated with positive well–being at the daily level. In contrast, the daily association between ethnic identity salience and well–being was less strong for youths who were low in ethnic identity. Additionally, a higher level of salience and a weaker association between salience and negative symptoms was found for girls than for boys, and older youths reported a weaker association between salience and positive symptoms than did younger youths.

Overview

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Crossref · 10.1111/1467-8624.00490

Cites

52 of 52 references verified0 citation errors · 0 not checkable

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Citations

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Metadata

Authors
Yip, T., & Fuligni, A. J.
Affiliations
  • New York University
  • University of California , Los Angeles
Venue
Child Development
Publisher
Oxford University Press (OUP)
Published
2002-09-01
Volume
73
Issue
5
Pages
1557-1572
ISSN
  • 0009-3920
  • 1467-8624
DOI
10.1111/1467-8624.00490
Cited by
174
References
52
Language
en
Licence

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.