Evidence map›Paper›PMID 34260653›Full record

ArticlePloS one2021

Characterizing the sectoral development of cities.

Diego Rybski, Prajal Pradhan, Shade T Shutters, Van Butsic, Jürgen P Kropp

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Diego RybskiPotsdam Institute for Climate Impact Research-PIK, Member of Leibniz Association, Potsdam, Germany.ORCID 0000-0001-6125-7705
Prajal PradhanPotsdam Institute for Climate Impact Research-PIK, Member of Leibniz Association, Potsdam, Germany.ORCID 0000-0003-0491-5489
Shade T ShuttersSchool of Complex Adaptive Systems, Arizona State University, Tempe, AZ, United States of America.
Van ButsicDepartment of Environmental Science Policy and Management, University of California Berkeley, Berkeley, CA, United States of America.
Jürgen P KroppPotsdam Institute for Climate Impact Research-PIK, Member of Leibniz Association, Potsdam, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous research has identified a predictive model of how a nation's distribution of gross domestic product (GDP) among agriculture (a), industry (i), and services (s) changes as a country develops. Here we use this national model to analyze the composition of GDP for US Metropolitan Statistical Areas (MSA) over time. To characterize the transfer of GDP shares between the sectors in the course of economic development we explore a simple system of differential equations proposed in the country-level model. Fitting the model to more than 120 MSAs we find that according to the obtained parameters MSAs can be classified into 6 groups (consecutive, high industry, re-industrializing; each of them also with reversed development direction). The consecutive transfer (a → i → s) is common but does not represent all MSAs examined. At the 95% confidence level, 40% of MSAs belong to types exhibiting an increasing share of GDP from agriculture. In California, such MSAs, which we classify as part of an agriculture renaissance, are found in the Central Valley.

Indexed as

CitiesEconomic DevelopmentModels, TheoreticalAgricultureGross Domestic ProductIndustryPopulation

Identifiers

PMID34260653
PMCPMC8279297

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.