Evidence map›Paper›PMID 42234749›Full record

ArticleScience advances2026

Bivalent impact of social networks on overarming: Insights on the alignment between social and individual interests.

Feng Fu, Michael Herron, Daniel Rockmore

Abstract read
In one paragraph

Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Feng FuDepartment of Mathematics, Dartmouth College, Hanover, NH 03755, USA.ORCID 0000-0001-8252-1990
Michael HerronProgram in Quantitative Social Science, Dartmouth College, Hanover, NH 03755, USA.
Daniel RockmoreDepartment of Mathematics, Dartmouth College, Hanover, NH 03755, USA.ORCID 0000-0001-5411-9224

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drawing on evolutionary game theory, we present a stylized model of gun acquisition for individuals in a society where all have the right to bear arms. In our dynamic model, pairwise confrontations with attendant payoffs take place between individuals who are either armed or unarmed. Individual payoffs depend on the probability of confrontation, the choice to arm, and others' choices. We show that the likelihood of confrontation affects the optimal societal arming rate and the arming rate that occurs in equilibrium. The latter rate quickly surpasses the former one as the probability of confrontation increases, a phenomenon we call "overarming." This reflects a misalignment of individual and societal interests. We further show that spatial structures can exacerbate overarming, especially when individuals perceive a deteriorating social environment. Results from our base model and its extensions highlight the importance of understanding how fundamental behavioral dynamics and network heterogeneity influence individual decisions to acquire firearms, informing empirical research for mitigating overarming.

Indexed as

FirearmsSocial NetworkingGame TheoryHumansModels, Theoretical

Identifiers

PMID42234749
PMCPMC13232554

What OpenQuestion holds

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LicenceCC BY
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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.