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Record W4244198215 · doi:10.32920/ryerson.14664117.v1

Planning for affordable housing, its engagement with mixed use planning, and revising how affordability is defined

2021· preprint· en· W4244198215 on OpenAlexaboutno aff
Karla Moreno Tamayo

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
FundersU.S. Department of Housing and Urban Development
KeywordsAffordable housingGentrificationUrban planningLocal planningBusinessLow incomePublic economicsEconomic growthEconomicsEnvironmental planningEngineeringGeographyDemographic economicsCivil engineering

Abstract

fetched live from OpenAlex

Affordable housing has become synonymous with mixed-use planning within affordable housing strategies across Canada and the United States. This paper first looks to understand why planning for affordable housing has widely engaged with mixed-use planning, then looks to understand the resulting impacts by summarizing recent empirical research within the intersection of affordable housing and mixed-use planning, and outlining emerging themes. This paper finds that affordable housing that engages with mixed-use planning is often associated with gentrification efforts, displacement, and inequitable development. Specifically analyzing the role that definitions of affordability and applications of these definitions have in relation to gentrification efforts, displacement, and inequitable development, this paper finds that mixed-use, affordable housing developments that insist on using market-level measures of affordability will continue to demonstrate the potential to cater to market trends instead of the needs of low-income residents if intervening measures are not in place.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.019
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.128
GPT teacher head0.334
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2021
Admission routes1
Has abstractyes

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