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Cohort Measures of Internal Migration: Understanding Long-Term Trends

Overview of attention for article published in Demography, November 2017
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)

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Title
Cohort Measures of Internal Migration: Understanding Long-Term Trends
Published in
Demography, November 2017
DOI 10.1007/s13524-017-0626-7
Pubmed ID
Authors

Aude Bernard

Abstract

Internal migration intensities fluctuate over time, but both migration levels and trends show great diversity. The dynamics underpinning these trends remain poorly understood because they are analyzed almost exclusively by applying period measures to cross-sectional data. This article proposes 10 cohort measures that can be applied to both prospective and retrospective data to systematically examine long-term trends. To demonstrate their benefits, the proposed measures are applied to retrospective survey data for England that provide residential histories from birth to age 50 for cohorts born between 1918 and 1957. The analysis reveals stable lifetime migration for men but increased lifetime migration for women associated with earlier ages at moving in adulthood and a compression of intervals between consecutive moves. The proposed cohort measures provide a more comprehensive picture of migration behavior and should be used to complement period measures in exploring long-term trends. Increasing availability of retrospective and longitudinal survey data means that researchers can now apply the proposed measures to a wide range of countries.

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The data shown below were collected from the profiles of 4 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 25%
Student > Master 6 10%
Researcher 6 10%
Student > Bachelor 5 8%
Student > Doctoral Student 4 7%
Other 9 15%
Unknown 16 26%
Readers by discipline Count As %
Social Sciences 24 39%
Economics, Econometrics and Finance 9 15%
Psychology 4 7%
Agricultural and Biological Sciences 1 2%
Environmental Science 1 2%
Other 2 3%
Unknown 20 33%
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 03 December 2017.
All research outputs
#12,765,116
of 23,009,818 outputs
Outputs from Demography
#1,644
of 1,868 outputs
Outputs of similar age
#150,364
of 330,783 outputs
Outputs of similar age from Demography
#18
of 21 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,868 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.3. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 330,783 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 53% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.