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Record W3179031816 · doi:10.1002/jcop.22671

“I'm No Criminal, I'm Just Homeless”: The Greensboro Homeless Union's efforts to address the criminalization of homelessness

2021· article· en· W3179031816 on OpenAlex
Krista Craven, Sonalini Sapra, Justin Harmon, Marcus Hyde

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Community Psychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCarleton University
Fundersnot available
KeywordsCriminalizationCriminologyVariety (cybernetics)SociologyLaw enforcementEnforcementPoliticsCitizen journalismPolitical scienceLawPublic relations

Abstract

fetched live from OpenAlex

This paper examines how homelessness is criminalized in Greensboro, North Carolina, and the ways in which the Homeless Union of Greensboro (HUG) has contested such criminalization. This paper draws on data from a participatory action research study conducted between 2018 and 2020 by a group of researchers from two local universities and members of HUG. Findings from our study suggest that law enforcement officers in Greensboro use a vast array of laws to harass, ticket, and arrest people experiencing homelessness, particularly those who are Black. Findings also suggest that when individuals experiencing homelessness seek help for citations or arrests, it is challenging to access quality, affordable legal representation. This paper illustrates how HUG takes a multi-pronged approach to address the variety of policies and practices that target homeless people, particularly people of color, recognizing that systems change requires a multifaceted approach that adapts to dynamic social and political contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.137
GPT teacher head0.470
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it