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Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

Quantifying social segregation in large-scale networks.

Bjørn-Atle Reme¹, Andreas Kotsadam², Johannes Bjelland³

¹Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway. Bjorn-Atle.Reme@fhi.no.

Scientific Reports

|April 20, 2022

Summary

This summary is machine-generated.

Social segregation in Oslo is strong and robust, especially among the wealthiest, using mobile phone and income data. Findings hold true even when considering workplace exposure and in a South Asian city.

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Area of Science:

Urban Sociology
Computational Social Science
Data Science

Background:

Understanding social segregation is crucial for urban planning and social equity.
Traditional methods often lack granular data to capture complex segregation patterns.

Purpose of the Study:

To develop and apply a novel measure of social segregation.
To analyze the strength, robustness, and characteristics of social segregation in Oslo.
To investigate the impact of workplace exposure on segregation and validate findings in a different societal context.

Main Methods:

Combining anonymized mobile phone location data with income register data.
Analyzing spatial patterns and social network clustering.
Utilizing workplace location data to assess inter-strata exposure.

Main Results:

Social segregation in Oslo is significant and persistent.
The wealthiest segments of the population exhibit particularly clustered social networks.
Exposure to diverse social strata, even at workplaces, does not substantially weaken measured segregation.
Key findings are consistent across Oslo and a major South Asian city.

Conclusions:

The developed measure effectively quantifies social segregation.
High levels of social segregation exist, with distinct patterns among different income groups.
Societal context influences, but does not negate, the observed segregation patterns.