Emergency Management Think Tank Report June 7, 2023
Bibliographic record
Abstract
Emergency management is a complex, ever-evolving profession. Emergency management practitioners and stakeholders from the public, private, and non-profit sectors have a unique professional obligation and moral responsibility to both set and stay well ahead of emerging trends. In recognition of this responsibility and the evolving post-pandemic landscape, The Canadian Journal of Emergency Management (CJEM), Public Safety Canada, and Emergency Management Logistics Canada (EMLC) hosted a Think Tank under Chatham House rules on June 7th, 2023 with participants from coast to coast and across the private sector, academia, the Government of Canada, and non-governmental organizations (NGOs). The purpose of this Think Tank was to bring together individuals with diverse experiences and points of view to discuss and explore the future of emergency management (EM) in the Canadian context. CJEM and EMLC’s 2023 Think Tank was conducted in a conference space provided by Public Safety Canada in Ottawa, Ontario, and fostered an environment of open and candid discussions.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.116 | 0.044 |
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".