Evidence map›Paper›PMID 40839567›Full record

ArticlePloS one2025

A recipe for systems change: Predictive modeling and street-level bureaucracy among homeless services.

Curtis Smith, Moinak Bhaduri

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Curtis SmithSociology Department, Bentley University, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-3103-6634
Moinak BhaduriMathematical Sciences Department, Bentley University, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-7403-7242

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study analyzes the necessary components to managing a successful systems change by considering the processes of housing people experiencing homelessness across a range of geographic locations in the United States. Utilizing Michael Lipsky's notion of street-level bureaucracy, a nonprofit organization called RE!NSTITUTE™ challenges social service agencies to a "100-Day Challenge™" by granting front-line workers ownership of improving their work free from oversight from their administrators, which results in improved outcomes. This paper also gives legitimacy to existing models on systems change by using novel mathematical predictive modeling through using principles of conditional probability to recognize the best "recipe" for systems change. This quantitative approach achieves three key goals. Firstly, it confirms the existence of a hierarchy that suspects transformative change is the most crucial to bring about, followed by relational or mental changes, and imparts a data-driven concreteness to the theoretical model, revealing varying shares within each broad level. We innovate alternate quasi-periodic visuals whose impacts are lasting. Next, it offers (even under partial knowledge of the predictors) correlational guarantees that one may use while designing future studies: when changes in relationship, practice, and power dynamics are sure, for instance, changes in mental structures often follow with 50% chance. Finally, we point out, through change-point analysis, how shifts in the rate of reducing homelessness may be attributed to assignable causes such as understaffing, which can hamper successes and workers' ability to maintain consistent attendance. We quantify the impact of those shifts. Several instances of 100-Day Challenges™ across various regions of the U.S. are analyzed to unearth commonalities. Thefindings we offer stress that while variables such as changes in resources (or funding) are often emphasized to achieve social change, changes in practices and relationships (networking) are the most influential ingredients to achieve transformative systems change. The sustainment of workers in their positions is a key driver in maintaining growth in successfully relocating individuals experiencing homelessness.

Indexed as

HousingIll-Housed PersonsModels, TheoreticalOrganizations, NonprofitSocial WorkHumansUnited States

Identifiers

PMID40839567
PMCPMC12370027

What OpenQuestion holds

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LicenceCC BY
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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.