Evidence map›Paper›PMID 27535087›Full record

ArticleScientific reports2016

Increasing returns to scale: The solution to the second-order social dilemma.

Hang Ye, Shu Chen, Jun Luo, Fei Tan, Yongmin Jia, Yefeng Chen

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Hang YeCollege of Economics, Interdisciplinary Center for Social Sciences (ICSS), Zhejiang University, Hangzhou, China.
Shu ChenCollege of Economics, Interdisciplinary Center for Social Sciences (ICSS), Zhejiang University, Hangzhou, China.
Jun LuoSchool of Economics, Center for Economic Behavior and Decision-making (CEBD), Zhejiang University of Finance and Economics, Hangzhou, China.
Fei TanDepartment of Economics, Saint Louis University, St.Louis, USA.
Yongmin JiaCollege of Economics, Interdisciplinary Center for Social Sciences (ICSS), Zhejiang University, Hangzhou, China.
Yefeng ChenCollege of Economics, Interdisciplinary Center for Social Sciences (ICSS), Zhejiang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans benefit from extensive cooperation; however, the existence of free-riders may cause cooperation to collapse. This is called the social dilemma. It has been shown that punishing free-riders is an effective way of resolving this problem. Because punishment is costly, this gives rise to the second-order social dilemma. Without exception, existing solutions rely on some stringent assumptions. This paper proposes, under very mild conditions, a simple model of a public goods game featuring increasing returns to scale. We find that punishers stand out and even dominate the population provided that the degree of increasing returns to scale is large enough; consequently, the second-order social dilemma dissipates. Historical evidence shows that people are more willing to cooperate with others and punish defectors when they suffer from either internal or external menaces. During the prehistoric age, the abundance of contributors was decisive in joint endeavours such as fighting floods, defending territory, and hunting. These situations serve as favourable examples of public goods games in which the degrees of increasing returns to scale are undoubtedly very large. Our findings show that natural selection has endowed human kind with a tendency to pursue justice and punish defection that deviates from social norms.

Indexed as

Cooperative BehaviorPunishmentComputer SimulationGame TheoryHumansSelection, GeneticSocial BehaviorSocial Justice

Identifiers

PMID27535087
PMCPMC4989174

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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.