Evidence map›Paper›PMID 36922507›Full record

ArticleScientific data2023

LocalView, a database of public meetings for the study of local politics and policy-making in the United States.

Soubhik Barari, Tyler Simko

Full text readDataset
In one paragraph

Article in Scientific data, 2023. 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
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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

2 authors.

Soubhik BarariPh.D. Candidate, Department of Government, Harvard University, Cambridge, USA. sbarari@g.harvard.edu.
Tyler SimkoPh.D. Candidate, Department of Government, Harvard University, Cambridge, USA. tsimko@g.harvard.edu.ORCID 0000-0001-9382-7346

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the fundamental importance of American local governments for service provision in areas like education and public health, local policy-making remains difficult and expensive to study at scale due to a lack of centralized data. This article introduces LOCALVIEW, the largest existing dataset of real-time local government public meetings-the central policy-making process in local government. In sum, the dataset currently covers 139,616 videos and their corresponding textual and audio transcripts of local government meetings publicly uploaded to YouTube-the world's largest public video-sharing website-from 1,012 places and 2,861 distinct governments across the United States between 2006-2022. The data are processed, downloaded, cleaned, and publicly disseminated (at localview.net ) for analysis across places and over time. We validate this dataset using a variety of methods and demonstrate how it can be used to map local governments' attention to policy areas of interest. Finally, we discuss how LOCALVIEW may be used by journalists, academics, and other users for understanding how local communities deliberate crucial policy questions on topics including climate change, public health, and immigration.

Identifiers

PMID36922507
PMCPMC10015146

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read14
table measurements read1
identifiers read1
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.