Future Trends and the Economic Burden of Dementia in Manitoba: Comparison with the Rest of Canada and the World
Bibliographic record
Abstract
Dementia is a growing public health concern in Canada. This epidemic is linked to huge human and economic costs. The number of Manitobans (65+) with dementia in 2045 (47,021), representing 2.58% of the Manitoban population, will be 2.3 times that of the year 2015 (20,235). The number of cases of dementia in Manitoba grew by 20.7% from 2015 to 2025, 68.16% from 2015 to 2035 and at an alarming rate of 125% from 2015 to 2045. Importantly, the total economic burden of dementia in Manitoba is close to one billion USD and is expected to grow more than 28 billion USD during the year 2038. The focus of this review is to compare dementia rates and the financial burden of dementia in Manitoba with the rest of Canada and the world from 2012 to 2048.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".