Evidence map›Paper›PMID 35912315›Full record

ArticleCriminology : an interdisciplinary journal2022

Collective efficacy and the built environment.

Charles C Lanfear

Abstract read
In one paragraph

Article in Criminology : an interdisciplinary journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Collective efficacy and the built environment.Criminology : an interdisciplinary journal · 2022
    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

1 author.

Charles C LanfearUniversity of Oxford.ORCID https://orcid.org/0000-0001-5712-757X

Funding

T32 Data Science and Demography Training BSSRT32HD101442 · NICHD · UNIVERSITY OF WASHINGTON · PI Zack W Almquist, SARA R. CURRAN · 2020 to 2026
$2.0M
NICHD NIH HHS T32 HD101442
6 · The paper itself

Abstract

Collective efficacy is a prominent explanation for neighborhood crime concentrations. Just as crime is concentrated in particular neighborhoods, within-neighborhoods crime is concentrated in particular criminogenic locations. Research suggests criminogenic locations are determined by features of the built environment. This study links collective efficacy with situational opportunity to propose that collective efficacy facilitates the removal of criminogenic features of the built environment. I test this by examining associations 1) between past collective efficacy and present criminogenic features of the built environment, as well as 2) between those built environment features and crime, net of present collective efficacy. These are modeled using piecewise structural equations with generalized linear mixed-effect regressions on data from 1,641 blocks in 343 Chicago neighborhoods. Four types of police-reported crime are modeled using eight block-level built environment features in the 2003 Chicago Community Area Health Study (CCAHS; N = 3,074) and neighborhood collective efficacy from the CCAHS and the 1995 Project in Human Development in Chicago Neighborhoods (PHDCN) Community Survey (N = 7,672). Findings suggest neighborhoods with high collective efficacy maintain low rates of crime in part by limiting criminogenic built environment features, in particular, abandoned buildings. This crime control pathway is important because changes to the built environment are long lasting and reduce the need for future interventions against crime.

Indexed as

built environmentcollective efficacyroutine activitiessituational opportunity

Identifiers

PMID35912315
PMCPMC9303720

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.