pollution/public health/water supply Constructing community health and safety
Bibliographic record
Abstract
Access to a sufficient amount of safe water is taken for granted in industrialised nations. Yet, as multiple incidents of contaminated water supplies show, citizens of highly industrialised nations such as Canada may not have access to safe water—the deadly E. coli outbreak in Waterton, Ontario, being but the most visible among many. Municipal engineers may find themselves between enemy lines as they are asked to assess available data of very different, even incommensurable, types in an evaluation of alternative solutions of access to safe water. Such access also takes into account safety issues such as those concerning the environment and fire hazards. This article reports the results of a ten-year anthropological study of science and municipal engineering in the oftenacrimonious conflict over access to the municipal watermain and safe water in one Canadian community. In the history of the conflict, municipal engineers repeatedly found themselves between a rock and a hard place, having to evaluate conflicting knowledge claims of qualitative and quantitative nature from quite different sources about the quantity and quality of water available to a part of the community zoned rural area. In considering solutions, the municipal engineers had to take into account oftenconflicting constraints posed by the environment, economy and social justice. Several alternatives are proposed that allow the integration of quantitative and qualitative knowledge in decision making concerning the different safety issues linked to municipal water. 1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".