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Record W4409447525 · doi:10.69520/jipe.v7i1.233

Ontario Tenant Policy Review: Preliminary Findings through Process Mapping

2025· article· en· W4409447525 on OpenAlex
Chak Yiu Carlo Chan, Anthony Piscitelli

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of innovation in polytechnic education. · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsConestoga CollegeUniversity of Toronto
Fundersnot available
KeywordsProcess (computing)BusinessComputer scienceProcess managementProgramming language

Abstract

fetched live from OpenAlex

Maintaining good relationships between landlords and tenants helps to resolve conflicts and disputes. Good tenant policies pushed forward created by socially responsible landlords are also crucial to protecting tenants from eviction. This paper uses process mapping to answer the following questions specifically within the Ontario context: 1) Where and how do landlords and tenants interact? What are the common issues and conflicts involved in these interactions? And 2) What can be done to de-escalate these issues and conflicts? In the process map, all the processes of a tenancy lifecycle are described, including the conflict points, possible outcomes and suggested remedies for each process. The process map presented is designed to improve the relationship between landlords and tenants through the collective efforts of stakeholders, such as housing organizations, tenant advisory committees, individual landlords, tenants, and housing providers. Ultimately, the process map provides tools—so socially responsible landlords can address tenants’ needs and protect tenants’ rights.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.689
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.363
Teacher spread0.342 · 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