Evidence map›Paper›PMID 39382002›Full record

ArticleThe British journal of sociology2025

Meritocratic beliefs in the United States, Finland, and China: A multidimensional approach using latent class analysis.

Li Zhu

Abstract read
In one paragraph

Article in The British journal of sociology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

1 author.

Li ZhuBerkeley School of Education, University of California, Berkeley, California, USA.ORCID https://orcid.org/0000-0003-0179-6496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study employs latent class analysis (LCA) as a novel methodology to investigate the multidimensional nature of meritocratic beliefs, addressing the limitations of traditional unidimensional approaches. Using data from the International Social Survey Program 2009 for the United States, Finland, and China, this study demonstrates several advantages of this multidimensional approach. First, LCA effectively identifies dual consciousness, where individuals simultaneously endorse meritocratic and structuralist explanations of social stratification. The analysis reveals three distinct narratives explaining social stratification: purely meritocratic beliefs, predominantly meritocratic beliefs, and dual consciousness. While all three subtypes consider merits highly important, they differ in their perceived importance of structural factors. Second, LCA facilitates cross-national comparisons, unveiling qualitative typological variations in meritocratic beliefs across countries. Unique country-specific subtypes or patterns emerge: Finland exhibits purely meritocratic beliefs, the United States shows predominantly meritocratic beliefs, and China demonstrates a dominance of dual consciousness. Although dual consciousness exists in all three countries, its prevalence varies significantly-dominant in China, moderate in the United States, and least in Finland. Third, this study reveals that the effect of education on meritocratic beliefs varies across the three countries. Education strengthens individual meritocratic beliefs in the United States, weakens them in Finland, and shows no significant effect in China. These findings highlight both within-country and across-country heterogeneity of meritocratic beliefs, underscoring the importance of a multidimensional approach.

Indexed as

Cross-Cultural ComparisonLatent Class AnalysisAdultChinaCultureEducational StatusFemaleFinlandHumansMaleMiddle AgedPoliticsSurveys and QuestionnairesUnited Statescross‐national studiesdual consciousnesseducationlatent class analysismeritocratic beliefssocial stratification

Identifiers

PMID39382002
PMCPMC11717172

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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.