Evidence map›Paper›PMID 34108786›Full record

ArticlePolicy studies journal: the journal of the Policy Studies Organization2016

Analyzing Policy Networks Using Valued Exponential Random Graph Models: Do Government-Sponsored Collaborative Groups Enhance Organizational Networks?

Tyler A Scott

Abstract read
In one paragraph

Article in Policy studies journal: the journal of the Policy Studies Organization, 2016. 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

1 author.

Tyler A ScottPublic Policy in the School of Public and International Affairs at the University of Georgia.

Funding

Methods and Data CoreR24HD042828 · NICHD · UNIVERSITY OF WASHINGTON · PI CURRAN, SARA R. · 2002 to 2016
$9.3M
Scientific/Technical CoreP2CHD042828 · NICHD · UNIVERSITY OF WASHINGTON · PI SARA R. CURRAN · 2017 to 2026
$6.3M
NICHD NIH HHS P2C HD042828NICHD NIH HHS R24 HD042828
6 · The paper itself

Abstract

This paper examines collaborative management groups from the perspective of policymakers seeking to increase coordination within a policy network. While governments often support collaborative groups as a tool to address perceived network failures such as a lack of coordination, the net impact groups have is unclear. I use valued exponential random graph models (ERGMs) to model relationships of varying strength among a regional network of organizations involved in 57 collaborative groups. This provides a unique opportunity to study the interplay between numerous groups and organizations within a large-scale network. Valued ERGMs are a recently developed extension of standard ERGMs that model valued instead of binary ties; thus, this paper also makes a methodological contribution to the policy literature. Findings suggest that participation in collaborative groups does motivate coordination and cooperation amongst individual network organizations; however, this effect is strongest for: (i) organizations that are not already members of another group and (ii) organizations that do not have a preexisting tie. These results support a transaction-cost-based perspective of how government-sponsored collaborative groups can influence network coordination; further, they also provide an empirical example of the Ecology of Games, in which multiple collaborative institutions have interactive effects on one another within a policy network.

Indexed as

collaborative governancecollaborative managementERGMsnetwork analysispolicy networksvalued networks

Identifiers

PMID34108786
PMCPMC8186521

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Registered trials

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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.