Evidence map›Paper›PMID 40537544›Full record

ArticleScientific data2025

City-Defined Neighborhood Boundaries in the United States.

Stephen Ansolabehere, Jacob R Brown, Ryan D Enos, Ben Shair, Tyler Simko, David Sutton

Abstract readDataset
In one paragraph

Article in Scientific data, 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

6 authors.

Stephen AnsolabehereHarvard University, Department of Government, Cambridge, MA, 02138, USA.
Jacob R BrownBoston University, Department of Political Science, Boston, MA, 02215, USA. jbrown13@bu.edu.ORCID 0000-0001-8037-5360
Ryan D EnosHarvard University, Department of Government, Cambridge, MA, 02138, USA.
Ben ShairUniversity of Rochester, Rochester, NY, 14627, USA.
Tyler SimkoPrinceton University, Department of Politics, Princeton, NJ, 08544, USA.
David SuttonHarvard University, Department of Government, Cambridge, MA, 02138, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neighborhoods are frequently cited as impactful for social, economic, political, and health outcomes. Measuring neighborhoods, however, is challenging, as the definition of a neighborhood may change dramatically across places. Researchers lack widespread but locally-sourced data on neighborhoods, and instead often adopt widely available but arbitrary Census geographies as neighborhood proxies. Others invest in the collection of more precise definitions, but these types of data are hard to collect at scale. We address this tension between scale and precision by collecting, cleaning, and providing to researchers a new dataset of city-defined neighborhoods. Our data includes 206 of the largest cities in the United States, covering more than 77 million people. We combine these data with block-level Census demographic data and provide them along with open-source software to aid researchers in their use.

Indexed as

CitiesNeighborhood CharacteristicsResidence CharacteristicsCensusesHumansUnited States

Identifiers

PMID40537544
PMCPMC12179281

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.