Bibliographic record
Abstract
The purpose of this report is to recommend that City Council authorize the City Manager to enter into Mutual Aid Agreements (MAA) with Boards of Health to provide for public health mutual aid and assistance during emergencies. A recent request to enter into a MAA has been made by the Medical Officer of Health for the Simcoe-Muskoka Board of Health. The City of Toronto has an emergency management program spanning the broad scope of mitigation, preparedness, response and recovery activities, in compliance with the Emergency Management and Civil Protection Act. An important element of preparedness and response is to make arrangements that will ensure adequate assistance in the form of qualified personnel, services, equipment, or materials to initiate and sustain an effective emergency response. The Ontario Public Health Standards also encourage the use of formal Mutual Aid Agreements to enhance capacity that may be needed by Boards of Health. Such MAAs would allow for requests for assistance, the ability to accept offers to provide assistance or providing assistance to others based on the contents of the agreement, particularly as a way to mitigate capacity issues related to the need for credentialed and specialized staff skills during an emergency. The health and well-being of a community is best protected through the concerted efforts of multiple public health agencies providing assistance to one another when in need.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.384 | 0.275 |
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".