Commissioner The Walkerton Inquiry Prepared by:
Bibliographic record
Abstract
✴ This paper was commissioned by the Walkerton Inquiry. It is concerned, not so much with organizational failings in the Walkerton tragedy itself, as by the need to understand organizations at a general level. The lessons can be drawn by all concerned with the supply of safe drinking water in Ontario. The authors are students of people working together in organizations- not water specialists. As such, we have chosen to keep the discussion general in hopes of not moving beyond our sphere of competence. However, we believe that modern organizational theory has much to contribute to the design of the entities that supply water, treat wastes, measure environmental results and regulate the system. Modestly, we leave the readers to draw the conclusions for the specific organizations with which they are most concerned. This draft paper has been prepared as a background document for the Walkerton Inquiry. It is intended to generate and inform discussion about the safety of drinking water among parties with standing, relevant experts, and the public. It does not represent the findings, views or recommendations of the Commissioner. Written comments in response to the paper are welcome and will form part of the public record of the Inquiry. They should be submitted to:
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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 | 0.013 | 0.132 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.064 | 0.036 |
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".