Evidence map›Paper›PMID 38864335›Full record

ArticleProceedings. Biological sciences2024

The paradigm of tax-reward and tax-punishment strategies in the advancement of public resource management dynamics.

Lichen Wang, Yuyuan Liu, Ruqiang Guo, Liang Zhang, Linjie Liu, Shijia Hua

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Lichen WangCollege of Science, Northwest A&F University, Yangling 712100, People's Republic of China.
Yuyuan LiuCollege of Science, Northwest A&F University, Yangling 712100, People's Republic of China.ORCID 0009-0003-4681-582X
Ruqiang GuoCollege of Science, Northwest A&F University, Yangling 712100, People's Republic of China.
Liang ZhangCollege of Science, Northwest A&F University, Yangling 712100, People's Republic of China.
Linjie LiuCollege of Science, Northwest A&F University, Yangling 712100, People's Republic of China.ORCID 0000-0003-0286-8885
Shijia HuaCollege of Science, Northwest A&F University, Yangling 712100, People's Republic of China.ORCID 0000-0002-8230-060X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In contemporary society, the effective utilization of public resources remains a subject of significant concern. A common issue arises from defectors seeking to obtain an excessive share of these resources for personal gain, potentially leading to resource depletion. To mitigate this tragedy and ensure sustainable development of resources, implementing mechanisms to either reward those who adhere to distribution rules or penalize those who do not, appears advantageous. We introduce two models: a tax-reward model and a tax-punishment model, to address this issue. Our analysis reveals that in the tax-reward model, the evolutionary trajectory of the system is influenced not only by the tax revenue collected but also by the natural growth rate of the resources. Conversely, the tax-punishment model exhibits distinct characteristics when compared with the tax-reward model, notably the potential for bistability. In such scenarios, the selection of initial conditions is critical, as it can determine the system's path. Furthermore, our study identifies instances where the system lacks stable points, exemplified by a limit cycle phenomenon, underscoring the complexity and dynamism inherent in managing public resources using these models.

Indexed as

RewardTaxesHumansModels, TheoreticalPunishmentcommon resourceevolutionary game theorytax-punishmenttax-reward

Identifiers

PMID38864335
PMCPMC11286137

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.