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Record W4406057520 · doi:10.5206/ijoh.2023.3.16835

Fostering Community Resilience and Social Inclusion in the Face of Anti-Homeless NIMBYism

2025· article· en· W4406057520 on OpenAlexaffvenue
Marcus A. Sibley, Carrie B. Sanders, Natasha Martino, Erin Dej, Samantha Henderson

Bibliographic record

VenueInternational Journal on Homelessness · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcMaster UniversityUniversity of WaterlooWilfrid Laurier University
Fundersnot available
KeywordsResilience (materials science)Inclusion (mineral)Face (sociological concept)Community resilienceSociologyPsychologyGender studiesSocial scienceComputer science

Abstract

fetched live from OpenAlex

Homelessness has been framed as a growing crisis. People experiencing homelessness often face social exclusion and isolation as a result of policies and practices that promote a “Not in My Backyard” (NIMBY) philosophy. NIMBYism is most recognizable in its efforts to actively oppose affordable housing projects and challenge the efficacies of social servicing in the name of preserving existing neighbourhood dynamics and maintaining property values. These exclusionary discourses and practices have been challenged by a countermovement known as “Yes in my Backyard” (YIMBYism), which advocates for equitable and inclusive housing options and more impactful community programming. To better highlight the tensions between these two movements, this paper provides one of the first comprehensive reviews of multidisciplinary literature on NIMBYism and YIMBYism as they relate to homelessness. We frame the comprehensive review within a community resilience framework —a term used in disaster and emergency management—to shed light on ways communities can foster and promote community resilience in the face of techniques of social and physical exclusion.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.444
Teacher spread0.377 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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