Looking for Evidence of Public Health's Role for Long-Term Evacuees
Bibliographic record
Abstract
Many Canadians have had personal experience of a major emergency or disaster at some point in their lifetime and close to a third of those affected were evacuated from their homes or communities. Most evacuations have lasted less than 2 weeks, but in some instances, people have been displaced for months or years. For example, hundreds of residents evacuated following flooding in Lake St. Martin, Manitoba in 2011, remain displaced today. In order to learn more about the roles and responses of public health for long-term evacuees (LTEs) in Canada, we conducted a narrative review of published English-language documents, beginning with literature specific to Canada and then expanding to include literature on other high-income countries. We found that while researchers have explored public health considerations in emergency preparedness, acute disaster management, and resettlement in these contexts there is a dearth of published evidence regarding the public health implications of prolonged evacuation and the public health responses to long-term evacuation in Canada and in other high-income countries. Because the public health needs of diverse populations of LTEs have not been fully investigated, it is likely that they are neither well-understood nor adequately addressed in public health policy and practice.
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 | 0.010 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".