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Record W4308882186 · doi:10.1177/08854122221137859

The Role of Local Housing Policies in Preventing Displacement: A Literature Review

2022· review· en· W4308882186 on OpenAlexaff
Karen Chapple, Anastasia Loukaitou‐Sideris, Andrew H. Miller, Cody Zeger

Bibliographic record

VenueJournal of Planning Literature · 2022
Typereview
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLeverage (statistics)Displacement (psychology)Production (economics)Affordable housingBusinessPublic housingEconomicsPublic economicsNatural resource economicsEconomic growthComputer scienceMicroeconomics

Abstract

fetched live from OpenAlex

Residential displacement impacts the quality of life, health, and economic outlook for households. Yet, there is little evidence on how housing policy works to prevent displacement. This literature review examines how 12 housing policies, encompassing household/neighborhood stabilization, affordable housing preservation, and housing production, mitigate displacement. We conclude that stabilization strategies have the most direct and immediate effect on mitigating direct displacement, while housing production and preservation strategies can decrease indirect and/or exclusionary displacement. However, production policies typically require strong markets and longer time spans. Though more research is needed, local governments can still leverage housing policies to prevent displacement.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.036
GPT teacher head0.374
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations21
Published2022
Admission routes1
Has abstractyes

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