Stories to the Surface: Revealing the Impacts of Hydroelectric Development in Manitoba
Bibliographic record
Abstract
By Caroline Fidan Tyler Doenmez. Manitoba, although known as one of Canada’s prairie provinces, is arguably more defined by its waterways. One story tells that the very name “Manitoba” was born from water, derived from the Cree words Manitou, “Great Spirit,” and wapow, “sacred water,” to describe the sound of waves crashing against an island on Lake Manitoba (Sinclair and Cariou 2011, 4–5). The Red and Assiniboine Rivers, two prominent entities of movement and memory, meet in the heart of the province’s capital city of Winnipeg. The northward-flowing Red River empties into Lake Winnipeg, the tenth-largest freshwater lake in the world. The northern area of the province is dappled and threaded with thousands of lakes, abundant rivers, and watersheds. It is here, in the north, that water has been harnessed and commodified as a source of energy by Manitoba Hydro for the past six decades. Today, according to provincial and Manitoba Hydro websites, a staggering 97 percent of electricity generated in Manitoba is derived from hydropower (Manitoba Hydro 2023a, 9).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".