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Record W2910964291 · doi:10.4095/215802

Urban environment and human health in the Lower Mainland

2004· report· en· W2910964291 on OpenAlexaboutno aff
Clyde Hertzman

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMainlandHuman healthGeographyBusinessEnvironmental healthMedicineArchaeology

Abstract

fetched live from OpenAlex

Three important population health issues for the Lower Mainland area are discussed. Variations in health status found across the Lower Mainland are outlined and given in greater detail within the City of Vancouver. Using a case study, issues in the quality of civic community in the Lower Mainland are addressed. The region's principal pollution-related public health issues are summarized. Two health problems associated with the chemical environment of the modern city have been demonstrated to pose large-scale threats to human health: lead exposures among children and threats to respiratory health from particulate air pollution. The paper argues that a willingness to respond to socio-economic disparities in health status in a constructive way, the level of awareness of significant local issues, and a willingness to tackle an issue (particulate air pollution) which imposes a significant health constraint on urban development are all tests of the quality of our civic community, and improving the quality of civic community should be an objective of urban development.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.083
GPT teacher head0.343
Teacher spread0.259 · 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
Published2004
Admission routes1
Has abstractyes

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