FIRST-YEAR OUTCOMES OF THE MOHLTC-FUNDED COMMUNITY PARAMEDICINE DEMONSTRATION PROJECTS
Bibliographic record
Abstract
In 2014, Ontario’s Ministry of Health and Long-Term Care (MOHLTC) invested $6 million to support the development of 30 Community Paramedicine (CP) Demonstration Projects across the province. This investment supported the development of a variety of locally driven models that could allow paramedics to fill unique care gaps, and better integrate care for vulnerable patients in their communities. The 30 funded projects focused on activities related to conducting assessments and referrals, preventative home visits and Wellness Clinics. In the first 15 months, a total of 19,077 patients were enrolled across the 30 projects that engaged 1865 paramedics and 381 local primary, home and community care providers. Community paramedics completed 32,807 assessments and achieved a 14% overall decrease in the volume of 911 calls from patients enrolled more than six-months in a program. Therefore, community paramedicine activities have the potential to improve patient and system outcomes.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".