Evidence map›Paper›PMID 40978089›Full record

ArticlePNAS nexus2025

Time-space dynamics of income segregation in the city of Milan.

Lavinia Rossi Mori, Vittorio Loreto, Riccardo Di Clemente

Abstract read
In one paragraph

Article in PNAS nexus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lavinia Rossi MoriCentro Ricerche Enrico Fermi, Via Panisperna 89/A, Rome 00184, Italy.ORCID https://orcid.org/0009-0000-5166-012X
Vittorio LoretoCentro Ricerche Enrico Fermi, Via Panisperna 89/A, Rome 00184, Italy.ORCID https://orcid.org/0000-0002-2506-2289
Riccardo Di ClementeComplex Connections Lab, Network Science Institute, Northeastern University London, London E1W 1LP, United Kingdom.ORCID https://orcid.org/0000-0001-8005-6351

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional approaches to urban income segregation focus on static residential patterns, often failing to capture the dynamic nature of social mixing at the neighborhood level. We leverage high-resolution location-based data from mobile phones to capture the interplay of three different income groups (high, medium, and low) based on their daily routines. The three income groups define a novel 3D space embedded in the temporal dynamics of urban activities, which we propose as a framework to analyze social mixing. This framework offers a more detailed perspective on social interactions, closely linked to the geographical features of each neighborhood. While nighttime residential patterns show high segregation, the working hours foster inclusion, with the city center showing heightened levels of interaction. As evening sets in, leisure areas emerge as potential facilitators for social interactions, depending on urban features such as public transport and various Points Of Interest. These characteristics significantly modulate the magnitude and type of social stratification involved in social mixing, underscoring the significance of urban design in bridging or widening socio-economic divides.

Indexed as

GPSincome segregationmobilitysocial mixingurban planning

Identifiers

PMID40978089
PMCPMC12449691

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.