Evidence map›Paper›PMID 27713725›Full record

ArticleFrontiers in psychology2016

A Price Paid for Our Internal Strife: Escalated Intragroup Aggression and the Evolution of Ingroup Derogation.

Qi Wu, Wang Liu, Chen Li, Xiongfeng Li, Ping Zhou

Abstract read
In one paragraph

Article in Frontiers in psychology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Qi WuCognition and Human Behavior Key Laboratory of Hunan Province, Department of Psychology, Hunan Normal University Changsha, China.
Wang LiuCognition and Human Behavior Key Laboratory of Hunan Province, Department of Psychology, Hunan Normal University Changsha, China.
Chen LiCognition and Human Behavior Key Laboratory of Hunan Province, Department of Psychology, Hunan Normal University Changsha, China.
Xiongfeng LiCognition and Human Behavior Key Laboratory of Hunan Province, Department of Psychology, Hunan Normal University Changsha, China.
Ping ZhouCognition and Human Behavior Key Laboratory of Hunan Province, Department of Psychology, Hunan Normal University Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From evolutionary reasoning, we derived a novel hypothesis that ingroup derogation is an adaptation to a special ecological condition in which the greater threat of aggression is incurred by ingroup members. This hypothesis was tested and supported across five studies. Specifically, the computational modeling found that ingroup derogation could easily evolve if the chance of death incurred by intragroup conflicts was no less than 10%. Further behavioral experiments on Chinese participants showed that the ingroup derogation mechanism responded to heuristic social category cues and it responded more strongly when participants subjectively felt more vulnerable to interpersonal aggression, or when there were contextual cues of aggression in the immediate environment. Additional results showed that Chinese participants responded more strongly to aggression cues originating from ingroup members and that they endorsed more ingroup derogation attitudes even when the ingroup and outgroup members were both displaying cues of aggression. In addition, the results also revealed that the Chinese participants perceived more intentions of aggression from ingroup members than from outgroup members even in the absence of any clear signs of those intentions, and such a bias was positively correlated with ingroup derogation attitudes. Taken together, these results suggest that ingroup derogation is related to the evolved response of intragroup aggression management system.

Indexed as

evolutioningroup derogationintragroup aggressionPenna modelthreat management system

Identifiers

PMID27713725
PMCPMC5031712

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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.