Human health and environmental risk assessments: politics or science?
Bibliographic record
Abstract
Human Health and Environmental Risk Assessments are being used by both governments and \nindustries to determine whether or not existing and/or proposed pollution levels are safe for \nhuman populations and/or the natural environment. My personal experiences with a “Community \nBased Risk Assessment” in Sudbury, Ontario, Canada, left me rather doubtful as to the validity \nof both the science involved and the level of community involvement in the process. After \nmeeting other people who had participated in the same kind of process in other communities, I \ncame to the conclusion that these three risk assessments needed to be analyzed and chronicled, \nnot only for historical purposes, but as a reference to how the process was carried out in the three \ncommunities in question: Sudbury and Port Colborne, Ontario, and Belledune, New Brunswick. \nThe risk assessment in Sudbury, Ontario, resulted in the highest permissible levels of ambient \nnickel air pollution in the province to become the norm only for Sudbury. Of note, extensive \nwater pollution of multiple heavy metals was left out, at the insistence of the mining industry \npolluters, who not only funded the process, but were allowed to be involved. The Government of \nCanada would later charge one of the polluters, Vale, for allowing exactly this kind of pollution \nto occur. Areas of the Belledune fishery are now unfit for human consumption after being \nsubjected to “risk free” pollution; however, rather than close the lobster fishery, all lobsters \ncaught within a 4-mile radius of the smelter in Belledune, are bought by the polluter, and then \nincinerated, rather than face the public relations fallout of having to close the fishery. Another \ncase in point concerning contamination levels being increased to match local levels, as opposed \nto recognized standards, is the case of the nuclear accident in Fukushima, Japan. The accident \noccurred while research into the three CBRAs mentioned was being carried out. These cases \nclearly indicate human health and environmental risk assessments are a political process, not a \nscientific one, and meant to match whatever form and level of local contamination was \noccurring, in order to keep corporate profits and government tax revenues flowing, despite the \nvery real risks to human health and the environment
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.097 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.100 |
| Scholarly communication | 0.028 | 0.043 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.022 | 0.034 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".