Evidence map›Paper›PMID 34149569›Full record

ArticleFrontiers in psychology2021

Third-Party Punishment or Compensation? It Depends on the Reputational Benefits.

Zhuang Li, Gengdan Hu, Lei Xu, Qiangqiang Li

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. 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

4 authors.

Zhuang LiDepartment of Psychology, School of Humanities, Tongji University, Shanghai, China.
Gengdan HuDepartment of Psychology, School of Humanities, Tongji University, Shanghai, China.
Lei XuElectrical College, Shanghai Dianji University, Shanghai, China.
Qiangqiang LiDepartment of Psychology, School of Humanities, Tongji University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Third-party fairness maintenance could win some reputational benefits, and it includes two methods: punishment and compensation. We predicted that the third parties' preference between punishment and compensation are affected by whether they are free to choose between the two methods, and the affection could be interpreted through reputational benefits. The present study includes two sections. In Study 1, the participants acted as fourth parties who were asked to rate the reputations of the third parties who had chosen different response methods to an unfair result of the dictator game. The results showed that (1) there was no reputational difference between the two methods when third parties were not free to choose, (2) but the reputation of compensation was better when third parties were free to choose. In Study 2, the participants acted as third parties. The participants were asked to choose a method to respond to an unfair result of the dictator game. There were two reputational contexts: secret and open. The results showed that (1) when third parties were not free to choose, they had no preference between the two methods under the two reputational contexts, (2) but when third parties were free to choose freely, they prefer punishment under the secret context but prefer compensation under the open context. This study systematically reveals a reputational interaction between fourth and third parties, and verifies the affection of reputational benefits on the third parties' preference between punishment and compensation.

Indexed as

compensationfourth partypunishmentreputationthird-party fairness maintenance

Identifiers

PMID34149569
PMCPMC8211016

What OpenQuestion holds

Textmetadata
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.