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Record W4386823775 · doi:10.32920/24085251.v1

Tenants rights and high-rise retrofits: policy considerations for Toronto

2023· preprint· en· W4386823775 on OpenAlexaffabout
E.I.F. Pearce

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPublic housingUnit (ring theory)GentrificationAffordable housingFuel povertyBusinessEconomic growthEconomicsPsychology

Abstract

fetched live from OpenAlex

This paper examines the existing policies that support the completion of energy efficient retrofits (EERs) in multi-unit high-rise residential buildings in Toronto, Ontario. The completion of EERs in high-rise buildings is important for supporting the City’s objectives with respect to climate, housing, poverty reduction and resilience. However, despite the interrelation of EERs with the advancement of social policy objectives, tenant support and engagement throughout the EER process is inadequate in existing EER policy. This paper asserts the importance of tenant-focused EERs to the realization of anticipated energy performance post-retrofit to mitigating gentrification effects produced by EERs. Incorporating case studies of EER projects in other jurisdictions, as well as best practices developed by tenant advocacy groups and research organizations, this paper provides recommendations for policy and practice that support tenant-focused EERs in Toronto. Key words: Energy Efficiency, Retrofitting, Multi-Unit Residential, Urban Planning Policy, Tenant Rights, Environmental Justice

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.006
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0140.000

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 head0.060
GPT teacher head0.270
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes2
Has abstractyes

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