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Addressing the Housing Policy Divide: A Study of International Agricultural Worker Accommodation Standards in Ontario

2025· article· en· W4408764459 on OpenAlexaffvenueabout
Damilola Oyewale, Ryan Gibson

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAccommodationAgricultureBusinessAgricultural economicsEnvironmental planningEconomicsGeographyPsychology

Abstract

fetched live from OpenAlex

Housing conditions for International Agricultural Workers across Ontario municipalities reveal concerning inconsistencies in standards and enforcement. This study examines the regulatory framework governing worker housing in Southwestern Ontario, highlighting critical gaps between provincial policy directives and municipal implementation. Through document analysis of the Provincial Policy Statement and semi-structured interviews with municipal stakeholders, we identify systemic barriers to establishing consistent housing standards. Our thematic analysis reveals three key challenges: the absence of standardized provincial guidelines, inconsistent municipal approaches to housing regulations, and limited policy direction within the Provincial Policy Statement regarding agricultural worker accommodation. The research findings point to necessary policy reforms at both provincial and municipal levels. Recommendations include strengthening the Provincial Policy Statement with explicit standards for agricultural worker housing, enhancing provincial oversight of municipal housing regulations, and developing targeted resources for local enforcement. For planning practitioners, the study suggests proactive engagement with worker advocacy groups and regular review of municipal bylaws to ensure housing standards meet worker needs. These insights offer a foundation for developing more equitable housing policies that recognize the essential role of International Agricultural Workers in Ontario's agricultural sector.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.693

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0110.004
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.079
GPT teacher head0.403
Teacher spread0.324 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

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