MétaCan
Menu
Back to cohort
Record W2914374442 · doi:10.17269/s41997-019-00191-7

Advocating for improvements to building codes for the population’s health

2019· article· en· W2914374442 on OpenAlexaffvenue
Nancy Edwards, James Chauvin, Rosanne Blanchet

Bibliographic record

VenueCanadian Journal of Public Health · 2019
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of AlbertaPublic Works and Government Services CanadaUniversity of Ottawa
Fundersnot available
KeywordsFraming (construction)NormativePublic healthBuilt environmentBuilding codeOccupational safety and healthPublic relationsCode (set theory)StairsPoison controlConstruction industryEngineeringHuman factors and ergonomicsEnvironmental healthBusinessPolitical scienceArchitectural engineeringComputer securityComputer scienceMedicineConstruction engineeringNursingCivil engineeringLaw

Abstract

fetched live from OpenAlex

Construction codes are a major component of building codes. They provide normative standards by which buildings are designed, built, altered, inspected, and assessed. Persistently high, fall-related injury rates on stairs and in bathrooms indicate that public health advocacy is needed to enhance the passive protection of these codes. Targets and strategies for code improvement advocacy by public health professionals, organizations, and associations are discussed. Approaches pertinent to describing the problem, proposing solutions, and framing the message are considered. Attention is given to issues that may be particularly challenging for advocates. These include the need to address minimum standards, tackling gaps in injury-related surveillance data that may be used by the building industry to rebut proposed code changes, describing how construction code changes align with other progressive legal tools that shape our built environments, and considering which sector pays and which sector benefits from code improvements. Ergonomic and epidemiologic evidence indicates that construction code improvements can reduce falls and fall-related injuries. Public health advocates have an important role to play in strengthening these codes.

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)0.009
metaresearch head score (Gemma)0.002
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 score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
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 head0.081
GPT teacher head0.408
Teacher spread0.327 · 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

Citations8
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Public HealthSame topicInjury Epidemiology and PreventionFrench-language works237,207