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Record W2040514063 · doi:10.3390/insects2030343

Analysis of 44 Cases before the Landlord and Tenant Board Involving Bed Bug Infestations in Ontario, Canada: Focus on Adjudicator Decisions Based on Entomological/Pest Management Evidence and Accountability under the Residential Tenancy Act and Other Applicable Legislation

2011· article· en· W2040514063 on OpenAlexaboutno aff
Sam Bryks

Bibliographic record

VenueInsects · 2011
Typearticle
Languageen
FieldMedicine
TopicDermatological diseases and infestations
Canadian institutionsnot available
Fundersnot available
KeywordsLandlordAccountabilityBusinessLawPolitical science

Abstract

fetched live from OpenAlex

The resurgence of bed bugs in major urban centres in North America has resulted in conflict between landlords and tenants. This is commonly focused on attribution of blame for source of infestation, on responsibility, on costs for preparation, treatment and losses, and for compensation as rent abatement and/or alternative temporary housing. In Ontario, Canada, these issues are often decided by adjudicators at the Landlord and Tenant Board hearing claims, counter-claims and defense by legal representation (lawyers and paralegals) as well as through mediation. Evidence in these hearings may include photographs, invoices for costs as well as testimony by tenants, landlords and "expert witnesses" who are most often pest control firms representing their landlord clients. A total of 44 Landlord and Tenant Board adjudicated cases available online were analyzed. The analysis included elements of the decisions such as adjudicator, claimant (landlord or tenant), basis of claim, review of evidence, amount of claim, amount awarded, and evaluation of the quality of the evidence. The results of the analysis of these findings are discussed. Recommendations for improvement of adjudicator decisions on the basis of knowledge of bed bug biology and Integrated Pest Management best practices are presented as well as the importance of education of tenants and landlords to a process of mutual trust, support and accountability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.064
GPT teacher head0.290
Teacher spread0.226 · 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 designObservational
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

Citations3
Published2011
Admission routes1
Has abstractyes

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