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Record W4242642905 · doi:10.32920/ryerson.14663631.v1

Human Health Risk Assessment of Ambient Air in a Dispute Over Petrochemical Emissions

2021· preprint· en· W4242642905 on OpenAlexaffabout
Douglas Theodore Cousins

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsUniversity of GuelphToronto Metropolitan University
Fundersnot available
KeywordsRisk assessmentHealth risk assessmentContext (archaeology)Environmental planningIndigenousRisk managementEnvironmental healthPopulationPopulation healthHealth impact assessmentEnvironmental resource managementHealth riskBusinessRisk analysis (engineering)Environmental scienceGeographyPublic healthMedicineComputer scienceArchaeology

Abstract

fetched live from OpenAlex

Combined air emissions from multiple petrochemical facilities operating in the area known as Chemical Valley in Sarnia, Ontario, Canada, have led to escalating concerns over health effects to nearby residents. By conducting a quantitative health risk assessment of ambient air data collected from 2008-2014, this thesis investigated whether current emissions are resulting in increased health risk for the population living near Chemical Valley. The results of this analysis are that health risks are slightly higher than levels considered acceptable for large populations, but are within levels often accepted for smaller groups based on the traditional risk assessment - risk management paradigm. Interpreting these results in the context of the literature about the science-policy interface, and environmental dispute resolution, this thesis highlights several problems with using the traditional risk assessment - risk management paradigm as the basis for decision-making in environmental disputes— particularly when the affected population is Indigenous.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.433
Teacher spread0.398 · 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 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
Published2021
Admission routes2
Has abstractyes

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