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Record W4225424205 · doi:10.1139/cjce-2021-0396

Transparency and efficiency in building code review. The case of Ontario, Canada

2022· article· en· W4225424205 on OpenAlexaffvenueabout
Gary E. Martin, Ruth McKay

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2022
Typearticle
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsCarleton University
Fundersnot available
KeywordsBuilding codeTransparency (behavior)Architectural engineeringContext (archaeology)Process (computing)Government (linguistics)RoofCode (set theory)EngineeringBuilt environmentBusinessCivil engineeringPublic administrationPolitical scienceComputer scienceGeographyLaw

Abstract

fetched live from OpenAlex

The paper reports findings from a study of building codes and the code change process in Canada. The context is attempts by insurers to change building codes at the national and Province of Ontario levels to make housing more resilient to high winds. The paper focuses on one code update intended to strengthen the roof-to-wall connection in low-rise wood-framed dwellings. The research began with an extensive review of research and government documents followed by discussions and interviews with key stakeholders in the process. The paper concludes that the process of upgrading residential building codes, especially in Ontario, could be more transparent and efficient by incorporating innovations and technology utilized by the International Code Council in the United States.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.831
Threshold uncertainty score1.000

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)0.0010.000

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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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.

Study designNot applicable
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

Citations1
Published2022
Admission routes3
Has abstractyes

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