Protecting the Health of First Nation Personnel at Contaminated Sites: A Case Study of Mid-Canada Radar Line Site 050 in Northern Canada
Bibliographic record
Abstract
Recently, First Nation (FN) organizations have entered into agreements with federal and provincial government representatives to remediate radar-line sites in Ontario. These agreements stipulated that FN people would take part in the site delineation and remediation process to gain job experience and economic benefits. One important aspect of the process was protecting FN personnel from contaminant exposure and thus, from potential negative health outcomes associated with the cleanup work itself. In this paper, we describe the safety precautions used by FN workers preparing Mid-Canada Radar Line (MCRL) Site 050 for Phase 2 of the delineation process and the health monitoring protocol that was tested. We measured concentrations of total polychlorinated biphenyls (PCBs as Aroclor 1260), 14 individual PCB congeners, p,p’-DDT, p,p’-DDE, nine other organochlorine pesticides, and lead in the blood of Fort Albany FN workers before they started work at Site 050 and approximately a week before they completed their three-month work period in the contaminated zone. No significant differences were found in the paired samples. These results indicate that the safety precautions taken were adequate for the work and the site in question. The monitoring protocol discussed here may be used as a template and modified to meet the specific needs of other projects. The results of this study are important because other Aboriginal groups have entered or will be entering into agreements with government organizations for the remediation of other MCRL sites in Ontario and across Canada. Key words: Mid-Canada Radar Line, remediation, First Nations, PCBs, occupational health RÉSUMÉ. Les stations de ligne radar désaffectées situées tant dans l’Arctique que dans le Subarctique canadiens seraient des
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".