Evidence map›Paper›PMID 39890957›Full record

ArticleScientific reports2025

A new electoral bottom-up model of institutional governance.

Carlos M Garrido, Francisco C Santos, Elias Fernández Domingos, Ana M Nunes, Jorge M Pacheco

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

5 authors.

Carlos M GarridoBioSystems and Integrative Sciences Institute, Faculdade de Ciências da Universidade de Lisboa Campo Grande, 1749-016, Lisbon, Portugal.
Francisco C SantosATP-group, 2744-016, Porto Salvo, Portugal.
Elias Fernández DomingosAI Lab, Computer Science Department, Vrije Universiteit Brussel, Pleinlaan 9, 3rd Floor, 1050, Brussels, Belgium.
Ana M NunesBioSystems and Integrative Sciences Institute, Faculdade de Ciências da Universidade de Lisboa Campo Grande, 1749-016, Lisbon, Portugal.
Jorge M PachecoATP-group, 2744-016, Porto Salvo, Portugal. jmpacheco@math.uminho.pt.

Funding

Fundação para a Ciência e a Tecnologia PTDC/MAT- APL/6804/2020
6 · The paper itself

Abstract

The sustainable governance of Global Risky Commons (GRC)-global commons in the presence of a sizable risk of overall failure-is ubiquitous and requires a global solution. A prominent example is the mitigation of the adverse effects of global warming. In this context, the Collective Risk Dilemma (CRD) provides a convenient baseline model which captures many important features associated with GRC type problems by formulating them as problems of cooperation. Here we make use of the CRD to develop, for the first time, a bottom-up institutional governance framework of GRC. We find that the endogenous creation of local institutions that require a minimum consensus amongst group members-who, in turn, decide the nature of the institution (reward/punishment) via an electoral process-leads to higher overall cooperation than previously proposed designs, especially at low risk, proving that carrots and sticks implemented through local voting processes are more powerful than other designs. The stochastic evolutionary game theoretical model framework developed here further allows us to directly compare our results with those stemming from previous models of institutional governance. The model and the methods employed here are relevant and general enough to be applied to a variety of contemporary interdisciplinary problems.

Indexed as

Collective risk dilemmaCooperationEvolutionary game theoryStochastic processes

Identifiers

PMID39890957
PMCPMC11785748

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.