Evidence map›Paper›PMID 33093554›Full record

ArticleScientific reports2020

An equity-oriented rethink of global rankings with complex networks mapping development.

Loredana Bellantuono, Alfonso Monaco, Sabina Tangaro, Nicola Amoroso, Vincenzo Aquaro, Roberto Bellotti

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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.

Loredana BellantuonoDipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "A. Moro", 70126, Bari, Italy.ORCID 0000-0002-1333-2675
Alfonso MonacoIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy.ORCID 0000-0002-5968-8642
Sabina TangaroIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy.
Nicola AmorosoIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy. nicola.amoroso@uniba.it.
Vincenzo AquaroDivision for Public Institutions and Digital Government, United Nations Department of Economic and Social Affairs (DESA), New York, NY, 10017, USA.
Roberto BellottiDipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "A. Moro", 70126, Bari, Italy.ORCID 0000-0003-3198-2708

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, world rankings are promoted and used by international agencies, governments and corporations to evaluate country performances in a specific domain, often providing a guideline for decision makers. Although rankings allow a direct and quantitative comparison of countries, sometimes they provide a rather oversimplified representation, in which relevant aspects related to socio-economic development are either not properly considered or still analyzed in silos. In an increasingly data-driven society, a new generation of cutting-edge technologies is breaking data silos, enabling new use of public indicators to generate value for multiple stakeholders. We propose a complex network framework based on publicly available indicators to extract important insight underlying global rankings, thus adding value and significance to knowledge provided by these rankings. This approach enables the unsupervised identification of communities of countries, establishing a more targeted, fair and meaningful criterion to detect similarities. Hence, the performance of states in global rankings can be assessed based on their development level. We believe that these evaluations can be crucial in the interpretation of global rankings, making comparison between countries more significant and useful for citizens and governments and creating ecosystems for new opportunities for development.

Identifiers

PMID33093554
PMCPMC7582917

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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.