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What is the impact of flexicurity on the chances of entry into employment for people with low education and activity limitations due to health problems? A comparison of 21 European countries using…

Overview of attention for article published in BMC Public Health, August 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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1 policy source
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13 X users

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Title
What is the impact of flexicurity on the chances of entry into employment for people with low education and activity limitations due to health problems? A comparison of 21 European countries using Qualitative Comparative Analysis (QCA)
Published in
BMC Public Health, August 2016
DOI 10.1186/s12889-016-3482-2
Pubmed ID
Authors

Mona C Backhans, Sarah Mosedale, Daniel Bruce, Margaret Whitehead, Bo Burström

Abstract

Employment and unemployment are key determinants of health inequalities and should be a priority when discussing policies to reduce such inequalities. Our aim is to investigate how flexicurity policies across European countries impact on the employment chances for people with low education and activity limitations. The longitudinal EU-SILC dataset, pooled 2005-2010, was used to calculate labour market outcomes. The sample consisted of 25 countries and 19,881 individuals. The employment transitions of non-employed people with activity limitations was followed from one year to the next, and the outcomes were rates of return-to work (RTW) among those with low education, and relative equality of RTW between those with low and high education (rate ratio, RR). Data on flexicurity policy and labour market factors were accessed from Eurostat and the OECD. As policy data was only available for OECD countries, the sample was reduced to 21 countries. Fuzzy-set QCA (Qualitative Comparative Analysis) was used to examine how different combinations of the components of flexicurity were linked to the two outcomes. Where high rates of RTW were achieved, high employment rates were always present. In five countries (the Nordic countries and the Netherlands) these factors coexisted with high expenditure on active labour market policies and social services in old age. In three others (The Czech Republic, UK and Estonia) they were combined with low employment protection and low benefit expenditure. For equality in RTW, low unemployment rates were combined with either high benefit expenditure, or low employment protection. We found two routes that lead to high RTW: we characterise these as the high road and the low road. Taking the low road (relaxing employment protection and limiting benefits) may be a tempting option for poorly performing countries. However, without measures to stimulate female employment it may not be enough as high overall employment is so important in enabling people with activity limitations to access the labour market. To achieve equality in RTW, it seems that as long as unemployment is low, either flexibility or security is sufficient.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 24%
Student > Master 8 11%
Student > Doctoral Student 8 11%
Researcher 5 7%
Student > Postgraduate 5 7%
Other 10 14%
Unknown 18 25%
Readers by discipline Count As %
Social Sciences 23 32%
Medicine and Dentistry 8 11%
Nursing and Health Professions 8 11%
Psychology 3 4%
Business, Management and Accounting 2 3%
Other 5 7%
Unknown 22 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 15 November 2023.
All research outputs
#2,744,008
of 25,002,811 outputs
Outputs from BMC Public Health
#3,262
of 16,674 outputs
Outputs of similar age
#46,442
of 351,636 outputs
Outputs of similar age from BMC Public Health
#92
of 409 outputs
Altmetric has tracked 25,002,811 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,674 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has done well, scoring higher than 80% 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 351,636 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 409 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.