Bibliographic record
Abstract
Abstract The Norman Wells Operation in the Northwest Territories, Canada, is applying for a renewal of its water licence. The facility has been in operation since the 1920s on the banks of the Mackenzie River. No changes to the water inputs and outputs, facility process, or its land use footprint are being contemplated. No significant changes to the water licence are being requested. What is new is that the regulator now requires that Traditional Knowledge studies be undertaken – even for operating facilities. Of what possible use could such a study be at a site operating for almost 100 years? Turns out, quite a bit. Traditional Knowledge has been used in Canada for Environmental Impact Assessments for a number of years to plan new projects. This would be a first at an operating site with a static footprint. How could we make the study a useful exercise for both the local communities and the operation itself? It was decided that rather than focusing on the operational footprint itself as is the more usual approach, this study would focus on the Mackenzie River. Specifically, what did the operation need to know about the River for emergency response planning? Traditional Knowledge workshops were held in the local town of Norman Wells and down-river in Fort Good Hope. Local organizations were asked to select elders and others knowledgeable of the Mackenzie River to participate. A detailed map of a 220 km stretch of the River around the operation was updated which highlights access points, areas of winter open water, which islands were ice-covered in winter, hunting cabins, wildlife use, sand bar movement and so on. As Traditional Knowledge is intellectual property which is often required to be held in confidence, consent was obtained from workshop participants for more open use. The map was brought to public consultation meetings to show what data had been gathered, and to provide an opportunity for all community members to add more information. At the suggestion of Fort Good Hope community members, an additional workshop was conducted by boat along the River between Fort Good Hope and Norman Wells with community elders and facility first responders. Important sites were visited, photographed and summary description sheets were prepared. Finally, members from surrounding communities were invited to observe and then provide their suggestions and observations during the de-brief of an on-river emergency response exercise workshop. Traditional Knowledge has enhanced Norman Wells Operation’s ability to respond to incidents on the Mackenzie River by providing valuable added detail to maps and one-on-one knowledge sharing with first responders. Additionally, it has provided a meaningful forum for local communities and the operation to discuss issues and share information that is of importance to both.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.026 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.019 |
| Insufficient payload (model declined to judge) | 0.051 | 0.019 |
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".