Daniel Cownden

2.1k total citations · 2 hit papers
17 papers, 1.1k citations indexed

About

Daniel Cownden is a scholar working on Sociology and Political Science, Experimental and Cognitive Psychology and Demography. According to data from OpenAlex, Daniel Cownden has authored 17 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Sociology and Political Science, 4 papers in Experimental and Cognitive Psychology and 4 papers in Demography. Recurrent topics in Daniel Cownden's work include Evolutionary Game Theory and Cooperation (10 papers), Evolutionary Psychology and Human Behavior (4 papers) and Language and cultural evolution (3 papers). Daniel Cownden is often cited by papers focused on Evolutionary Game Theory and Cooperation (10 papers), Evolutionary Psychology and Human Behavior (4 papers) and Language and cultural evolution (3 papers). Daniel Cownden collaborates with scholars based in United Kingdom, Sweden and Canada. Daniel Cownden's co-authors include Timothy Lillicrap, Colin J. Akerman, Douglas Tweed, Magnus Enquist, Kimmo Eriksson, Kevin N. Laland, Luke Rendell, Laurel Fogarty, Marcus W. Feldman and Robert Boyd and has published in prestigious journals such as Science, Nature Communications and Scientific Reports.

In The Last Decade

Daniel Cownden

17 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Why Copy Others? Insights from the Social Learning Strategies Tournament

2010 501 citations Luke Rendell, Robert Boyd et al. Science profile →
Random synaptic feedback weights support error backpropagation for deep learning

2016 366 citations Timothy Lillicrap, Daniel Cownden et al. Nature Communications profile →

Peers

Daniel Cownden

SPS

CN

EEE

AI

GENET

Takashi Ikegami Japan

José F. Fontanari Brazil

Markus Brede United Kingdom

Arend Hintze United States

Chrisantha Fernando United Kingdom

Simon T. Powers United Kingdom

Richard Dawkins United States

Jean‐Baptiste André France

Seth Bullock United Kingdom

Jason Noble United Kingdom

Takashi Ikegami Japan

Daniel Cownden

245 ×0.6

SPS

181 ×0.8

CN

107 ×0.5

EEE

168 ×0.9

AI

141 ×0.8

GENET

Citations per year, relative to Daniel Cownden Daniel Cownden (= 1×) peers Takashi Ikegami

Countries citing papers authored by Daniel Cownden

Since Specialization

Citations

This map shows the geographic impact of Daniel Cownden's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Cownden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Cownden more than expected).

Fields of papers citing papers by Daniel Cownden

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Cownden. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Cownden. The network helps show where Daniel Cownden may publish in the future.

Co-authorship network of co-authors of Daniel Cownden

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Cownden. A scholar is included among the top collaborators of Daniel Cownden based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Cownden. Daniel Cownden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

1.

Rendell, Luke, Daniel Cownden, Magnus Enquist, et al.. (2024). The refinement paradox and cumulative cultural evolution: Complex products of collective improvement favor conformist outcomes, blind copying, and hyper-credulity. PLoS Computational Biology. 20(9). e1012436–e1012436. 3 indexed citations

2.

Barra, Mícheál de, Daniel Cownden, & Fredrik Jansson. (2019). Aversive medical treatments signal a need for support: a mathematical model. Evolutionary Human Sciences. 1. e4–e4. 3 indexed citations

3.

Hogan, Thea, et al.. (2019). Differential impact of self and environmental antigens on the ontogeny and maintenance of CD4+ T cell memory. eLife. 8. 13 indexed citations

4.

Eriksson, Kimmo, Daniel Cownden, & Pontus Strimling. (2017). Social learning may lead to population level conformity without individual level frequency bias. Scientific Reports. 7(1). 17341–17341. 2 indexed citations

5.

Cownden, Daniel, Kimmo Eriksson, & Pontus Strimling. (2017). A popular misapplication of evolutionary modeling to the study of human cooperation. Evolution and Human Behavior. 38(3). 421–427. 5 indexed citations

6.

Hogan, Thea, et al.. (2017). Memory CD4 T cell subsets are kinetically heterogeneous and replenished from naive T cells at high levels. eLife. 6. 57 indexed citations

7.

Lillicrap, Timothy, Daniel Cownden, Douglas Tweed, & Colin J. Akerman. (2016). Random synaptic feedback weights support error backpropagation for deep learning. Nature Communications. 7(1). 13276–13276. 366 indexed citations breakdown →

8.

Cownden, Daniel, et al.. (2016). Sticklebacks show consistent prey share hierarchies within but not between patchy and sequential prey distributions. Journal of Zoology. 300(2). 137–141. 1 indexed citations

9.

Cownden, Daniel, Kimmo Eriksson, & Pontus Strimling. (2015). The implications of learning across perceptually and strategically distinct situations. Synthese. 195(2). 511–528. 1 indexed citations

10.

Whalen, Andrew, Daniel Cownden, & Kevin N. Laland. (2015). The learning of action sequences through social transmission. Animal Cognition. 18(5). 1093–1103. 11 indexed citations

11.

Cownden, Daniel & David Steinsaltz. (2014). Effects of Competition in a Secretary Problem. Operations Research. 62(1). 104–113. 5 indexed citations

12.

Eriksson, Kimmo, et al.. (2014). Altruisticc and Antisociall Punishers Are One and the Same. SSRN Electronic Journal. 1 indexed citations

13.

Kolk, Martin, Daniel Cownden, & Magnus Enquist. (2014). Correlations in fertility across generations: can low fertility persist?. Proceedings of the Royal Society B Biological Sciences. 281(1779). 20132561–20132561. 33 indexed citations

14.

Eriksson, Kimmo, et al.. (2014). 'Altruistic' and 'Antisocial' Punishers are One and the Same. Kent Academic Repository (University of Kent). 1(3). 209–221. 12 indexed citations

15.

Taylor, Peter, Timothy Lillicrap, & Daniel Cownden. (2010). INCLUSIVE FITNESS ANALYSIS ON MATHEMATICAL GROUPS. Evolution. 65(3). 849–859. 21 indexed citations

16.

Rendell, Luke, Robert Boyd, Daniel Cownden, et al.. (2010). Why Copy Others? Insights from the Social Learning Strategies Tournament. Science. 328(5975). 208–213. 501 indexed citations breakdown →

17.

Hurford, Amy, Daniel Cownden, & Troy Day. (2009). Next-generation tools for evolutionary invasion analyses. Journal of The Royal Society Interface. 7(45). 561–571. 96 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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