Evidence map›Paper›PMID 35282641›Full record

ArticleSustainability science2022

Region-income-based prioritisation of Sustainable Development Goals by Gradient Boosting Machine.

Atie Asadikia, Abbas Rajabifard, Mohsen Kalantari

Abstract read
In one paragraph

Article in Sustainability science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Atie AsadikiaSDGs Research Group, Centre for Spatial Data Infrastructures and Land Administration, Faculty of Engineering and IT, The University of Melbourne, Parkville, VIC 3010 Australia.
Abbas RajabifardSDGs Research Group, Centre for Spatial Data Infrastructures and Land Administration, Faculty of Engineering and IT, The University of Melbourne, Parkville, VIC 3010 Australia.ORCID https://orcid.org/0000-0002-4256-3173
Mohsen KalantariSDGs Research Group, Centre for Spatial Data Infrastructures and Land Administration, Faculty of Engineering and IT, The University of Melbourne, Parkville, VIC 3010 Australia.ORCID https://orcid.org/0000-0002-6650-5218

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Sustainable Development Goals (SDGs) seek to address complex global challenges and cover aspects of social development, environmental protection, and economic growth. However, the holistic and complicated nature of the goals has made their attainment difficult. Achieving all goals by 2030 given countries' limited budgets with the economic and social disruption that the COVID-19 pandemic has caused is over-optimistic. To have the most profound impact on the SDGs achievement, prioritising and improving co-beneficial goals is an effective solution. This study confirms that countries' geographic location and income level have a significant relationship with overall SDGs achievement. This article applies the Gradient Boosting Machine (GBM) algorithm to identify the top five SDGs that drive the overall SDG score. The results show that the influential SDGs vary for countries with a specific income level located in different regions. In Europe and Central Asia, SDG10 is among the most influential goals for high-income countries, SDG9 for upper-middle-income, SDG3 in low and lower-middle-income countries of Sub-Saharan Africa, and SDG5 in Latin America and the Caribbean upper-middle-income countries. This systematic and exploratory data-driven study generates new insights that confirm the uniqueness, and non-linearity of the relationship between goals and overall SDGs achievement.

Indexed as

Co-beneficial SDGsData scienceGradient boosting machineMachine learningSDG prioritisationSustainable development goals

Identifiers

PMID35282641
PMCPMC8900480

What OpenQuestion holds

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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.