The State of Knowledge about Grizzly Bears (Kakenokuskwe osow Muskwa (Cree), Ursus arctos) in Northern Manitoba
Bibliographic record
Abstract
Grizzly bears have been observed with increasing frequency in northern Manitoba, Canada over the last four decades (1980 – 2020), likely originating from the established population in Nunavut and the Northwest Territories. We summarize and present an interdisciplinary synthesis of documented observations of grizzly bears in northern Manitoba from historical records from the Hudson’s Bay Company Archives, published literature, direct observations, remote camera observations, government agency reports, the first author’s field notes, volunteered observations, and media and social media reports. A total of 160 observations were recorded, 140 of them since 1980. Spatially, these observations all fall within the Southern Arctic, Hudson Plains, and Taiga Shield ecozones within Manitoba and span from the northern limit of Manitoba at the Nunavut border to the south shore of the Nelson River. Grizzly bears were historically present in northern Manitoba prior to 1980, though in very low numbers, but the frequency of observations has increased significantly since then. Most observations (86%) were less than 1 km from the Hudson Bay coast. Grizzly bears appear to select for open habitats and against forested ones. Reported observations, however, have been largely opportunistic, and the geographical distribution of observer efforts was uneven, so our data likely contain spatial and temporal biases. All confirmed observations were of single bears, suggesting that the present population is likely maintained by dispersal from the population to the north. Understanding grizzly bear ecology, distribution, and demographics north and west of Churchill will be critical for more accurately assessing the status and conservation needs of grizzly bears in the province.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".