Evidence map›Paper›PMID 35468139›Full record

ArticlePloS one2022

Communities in world input-output network: Robustness and rankings.

Alexei Kireyev, Andrey Leonidov, Stanislav Radionov, Ekaterina Vasilyeva

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. 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
0.1field-weighted citation impact, top 60% of its field
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, 1 citations in OpenAlex.

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

4 authors at 2 institutions in 2 countries.

Alexei KireyevInternational Monetary Fund, Washington, DC, United States of America.
Andrey LeonidovTheoretical Physics Department, P.N. Lebedev Physical Institute, Moscow, Russia.
Stanislav RadionovTheoretical Physics Department, P.N. Lebedev Physical Institute, Moscow, Russia.
Ekaterina VasilyevaTheoretical Physics Department, P.N. Lebedev Physical Institute, Moscow, Russia.ORCID 0000-0002-9303-8424
P.N. Lebedev Physical Institute of the Russian Academy of Sciences · RUInternational Monetary Fund · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce a method for assessing the robustness of community detection and apply it to a world input-output network (WION) to obtain economically plausible results. This method enabled us to rank communities in the WION in terms of their robustness and stability. The algorithmic assignment variability index proposed in this study is shown to have predictive power in terms of forthcoming community rearrangement. We also provide several new approaches for identifying key economic communities. These approaches are based on the application of several centrality measures to a synthetic network in which nodes represent WION communities. Using these methods, we show that in 2000-2014, United States and Japan-centered communities demonstrated decreasing trends, while the importance of the China-centered community predominantly increased. A notable feature of the Germany-centered community rank evolution is that its influence grew only as a result of the inclusion of the Netherlands and Belgium in 2013.

Indexed as

Residence CharacteristicsAlgorithmsBelgiumChinaGermanyJapanNetherlands

Identifiers

PMID35468139
PMCPMC9037945
OpenAlexW4224597203

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.