Evidence map›Paper›PMID 37964528›Full record

ArticleProceedings. Biological sciences2023

Cultural transmission of move choice in chess.

Egor Lappo, Noah A Rosenberg, Marcus W Feldman

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Computers and chess masters: The role of AI in transforming elite human performance.British journal of psychology (London, England : 1953) · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Half a century of quantitative cultural evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  6. Cultural transmission of move choice in chess.Proceedings. Biological sciences · 2023
    Article
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

3 authors.

Egor LappoDepartment of Biology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-0847-4070
Noah A RosenbergDepartment of Biology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-1829-8664
Marcus W FeldmanDepartment of Biology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-0664-3803

Funding

National Science Foundation BCS-2116322
6 · The paper itself

Abstract

The study of cultural evolution benefits from detailed analysis of cultural transmission in specific human domains. Chess provides a platform for understanding the transmission of knowledge due to its active community of players, precise behaviours and long-term records of high-quality data. In this paper, we perform an analysis of chess in the context of cultural evolution, describing multiple cultural factors that affect move choice. We then build a population-level statistical model of move choice in chess, based on the Dirichlet-multinomial likelihood, to analyse cultural transmission over decades of recorded games played by leading players. For moves made in specific positions, we evaluate the relative effects of frequency-dependent bias, success bias and prestige bias on the dynamics of move frequencies. We observe that negative frequency-dependent bias plays a role in the dynamics of certain moves, and that other moves are compatible with transmission under prestige bias or success bias. These apparent biases may reflect recent changes, namely the introduction of computer chess engines and online tournament broadcasts. Our analysis of chess provides insights into broader questions concerning how social learning biases affect cultural evolution.

Indexed as

Social LearningHumansModels, Statisticalchesscultural evolutionDirichlet-multinomialsocial learningtransmission biases

Identifiers

PMID37964528
PMCPMC10646474

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.