↓ Skip to main content

Multidimensional poverty measure and analysis: a case study from Hechi City, China

Overview of attention for article published in SpringerPlus, May 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
118 Mendeley
Title
Multidimensional poverty measure and analysis: a case study from Hechi City, China
Published in
SpringerPlus, May 2016
DOI 10.1186/s40064-016-2192-7
Pubmed ID
Authors

Yanhui Wang, Baixue Wang

Abstract

Aiming at the anti-poverty outline of China and the human-environment sustainable development, we propose a multidimensional poverty measure and analysis methodology for measuring the poverty-stricken counties and their contributing factors. We build a set of multidimensional poverty indicators with Chinese characteristics, integrating A-F double cutoffs, dimensional aggregation and decomposition approach, and GIS spatial analysis to evaluate the poor's multidimensional poverty characteristics under different geographic and socioeconomic conditions. The case study from 11 counties of Hechi City shows that, firstly, each county existed at least four respects of poverty, and overall the poverty level showed the spatial pattern of surrounding higher versus middle lower. Secondly, three main poverty contributing factors were unsafe housing, family health and adults' illiteracy, while the secondary factors include fuel type and children enrollment rate, etc., generally demonstrating strong autocorrelation; in terms of poverty degree, the western of the research area shows a significant aggregation effect, whereas the central and the eastern represent significant spatial heterogeneous distribution. Thirdly, under three kinds of socioeconomic classifications, the intra-classification diversities of H, A, and MPI are greater than their inter-classification ones, while each of the three indexes has a positive correlation with both the rocky desertification degree and topographic fragmentation degree, respectively. This study could help policymakers better understand the local poverty by identifying the poor, locating them and describing their characteristics, so as to take differentiated poverty alleviation measures according to specific conditions of each county.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 118 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 19%
Student > Master 14 12%
Researcher 11 9%
Student > Doctoral Student 10 8%
Student > Bachelor 8 7%
Other 13 11%
Unknown 39 33%
Readers by discipline Count As %
Economics, Econometrics and Finance 31 26%
Social Sciences 11 9%
Agricultural and Biological Sciences 7 6%
Environmental Science 6 5%
Business, Management and Accounting 5 4%
Other 17 14%
Unknown 41 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 June 2016.
All research outputs
#12,961,619
of 22,879,161 outputs
Outputs from SpringerPlus
#623
of 1,850 outputs
Outputs of similar age
#158,492
of 326,837 outputs
Outputs of similar age from SpringerPlus
#69
of 192 outputs
Altmetric has tracked 22,879,161 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,850 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,837 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 192 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.