↓ Skip to main content

Immigrants and Italian labor market: statistical or taste-based discrimination?

Overview of attention for article published in Genus, February 2018
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
20 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Immigrants and Italian labor market: statistical or taste-based discrimination?
Published in
Genus, February 2018
DOI 10.1186/s41118-018-0030-1
Pubmed ID
Authors

Giovanni Busetta, Maria Gabriella Campolo, Demetrio Panarello

Abstract

Types of discrimination are usually distinguished by economic theory in statistical and taste-based. Using a correspondence experiment, we analyze which of the two affects Italian labor market the most. In this respect, we studied the difference in discrimination reserved to first- and second-generation immigrants, taking gender differences into account. Even if we want to admit a rational discrimination based on perceived productivity differences (statistical discrimination) against first-generation immigrants (concerning language and education gaps), the same would not be reasonable for second-generation ones. Since they are born and educated in Italy, where they have always lived, the associated discrimination must be taste-based.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 40%
Student > Ph. D. Student 3 15%
Student > Bachelor 2 10%
Other 1 5%
Lecturer 1 5%
Other 1 5%
Unknown 4 20%
Readers by discipline Count As %
Social Sciences 5 25%
Business, Management and Accounting 4 20%
Economics, Econometrics and Finance 3 15%
Computer Science 1 5%
Psychology 1 5%
Other 1 5%
Unknown 5 25%

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 29 August 2019.
All research outputs
#10,101,600
of 18,635,251 outputs
Outputs from Genus
#50
of 71 outputs
Outputs of similar age
#123,863
of 286,398 outputs
Outputs of similar age from Genus
#1
of 1 outputs
Altmetric has tracked 18,635,251 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 71 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 30th percentile – i.e., 30% 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 286,398 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 56% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them