Evidence map›Paper›PMID 29440527›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018

Divide and conquer: intermediate levels of population fragmentation maximize cultural accumulation.

Maxime Derex, Charles Perreault, Robert Boyd

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Decoding the Dynamics of Cultural Change: A Cultural Evolution Approach to the Psychology of Acculturation.Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc · 2025
    Review
  5. Article
  6. Cultural evolution, social ratcheting and the evolution of human division of labour.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
  7. Article
  8. Article
  9. Review
  10. 3.3 million years of stone tool complexity suggests that cumulative culture began during the Middle Pleistocene.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Maintaining Transient Diversity Is a General Principle for Improving Collective Problem Solving.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024
    Review
  13. Article
  14. Innovation-facilitating networks create inequality.Proceedings. Biological sciences · 2023
    Article
  15. Minority-group incubators and majority-group reservoirs support the diffusion of climate change adaptations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  16. Article
  17. Mechanisms of collective learning: how can animal groups improve collective performance when repeating a task?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
  18. How subcultures emerge.Evolutionary human sciences · 2023
    Article
  19. Article
  20. 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.

Maxime DerexInstitute of Human Origins, Arizona State University, Tempe, AZ 85287, USA maxime.derex@gmail.com.ORCID 0000-0002-1512-6496
Charles PerreaultInstitute of Human Origins, Arizona State University, Tempe, AZ 85287, USA.
Robert BoydInstitute of Human Origins, Arizona State University, Tempe, AZ 85287, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying the determinants of cumulative cultural evolution is a key issue in the interdisciplinary field of cultural evolution. A widely held view is that large and well-connected social networks facilitate cumulative cultural evolution because they promote the spread of useful cultural traits and prevent the loss of cultural knowledge through factors such as drift. This view stems from models that focus on the transmission of cultural information, without considering how new cultural traits actually arise. In this paper, we review the literature from various fields that suggest that, under some circumstances, increased connectedness can decrease cultural diversity and reduce innovation rates. Incorporating this idea into an agent-based model, we explore the effect of population fragmentation on cumulative culture and show that, for a given population size, there exists an intermediate level of population fragmentation that maximizes the rate of cumulative cultural evolution. This result is explained by the fact that fully connected, non-fragmented populations are able to maintain complex cultural traits but produce insufficient variation and so lack the cultural diversity required to produce highly complex cultural traits. Conversely, highly fragmented populations produce a variety of cultural traits but cannot maintain complex ones. In populations with intermediate levels of fragmentation, cultural loss and cultural diversity are balanced in a way that maximizes cultural complexity. Our results suggest that population structure needs to be taken into account when investigating the relationship between demography and cumulative culture.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'.

Indexed as

Cultural DiversityCultural EvolutionPopulation DensityHumansModels, Theoreticalcultural convergencecultural homogenizationinnovationpopulation structuresocial learningtechnological trajectory

Identifiers

PMID29440527
PMCPMC5812974

What OpenQuestion holds

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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.