Evidence map›Paper›PMID 40874030›Full record

ArticlePNAS nexus2025

What values best distinguish the world's cultures? The machine learning-based cultural values inventory.

Abhishek Sheetal, Shilpa Madan, Rui Ling Lee, Krishna Savani

Abstract read
In one paragraph

Article in PNAS nexus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

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

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

4 authors.

Abhishek SheetalFaculty of Business, The Hong Kong Polytechnic University, Li Ka Shing Tower, Hung Hom, Kowloon, Hong Kong.ORCID https://orcid.org/0000-0002-4585-5358
Shilpa MadanLee Kong Chian School of Business, Singapore Management University, 50 Stamford Road, Singapore 178899.ORCID https://orcid.org/0000-0001-8224-177X
Rui Ling LeeNanyang Business School, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798.
Krishna SavaniFaculty of Business, The Hong Kong Polytechnic University, Li Ka Shing Tower, Hung Hom, Kowloon, Hong Kong.ORCID https://orcid.org/0000-0002-6934-1917

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scientists studying culture typically focus on a small number of theoretical constructs, such as individualism-collectivism, when seeking to explain cultural differences in psychological tendencies and behaviors. However, existing theories of culture could have missed out on important constructs that are useful for explaining cross-cultural differences. We used an abductive approach combining prediction and explanation to uncover important cultural values. In the prediction phase, based on 594 attitudes, values, and beliefs included in the World Values Survey, a neural network could classify respondents' nationalities with 90% accuracy in out-of-sample data. In the explanation phase, a feature importance analysis identified the values that contributed the most to predicting individuals' countries of origin. The top 60 variables resulting from this analysis were used to create the

Indexed as

culturediscoveryexplanationmachine learningprediction

Identifiers

PMID40874030
PMCPMC12378846

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.