Canada COVID-19 Governmental Response
Bibliographic record
Abstract
The International Health Regulations (2005) are legally binding on 196 States Parties, Including all WHO Member States. The IHR aims to keep the world informed about public health risks, through committing all signatories to cooperate together in combating any future “illness or medical condition, irrespective of origin or source, that presents or could present significant harm to humans.” Under IHR, countries agreed to strengthen their public health capacities and notify the WHO of any such illness in their populations. The WHO would be the centralized body for all countries facing a health threat, with the power to declare a “public health emergency of international concern,” issue recommendations, and work with countries to tackle a crisis. Although, with the sudden and rapid spread of COVID-19 in the world, many countries varied in implementing the WHO guidelines and health recommendations. While some countries followed the WHO guidelines, others imposed travel restrictions against the WHO’s recommendations. Some refused to share their data with the organization. Others banned the export of medical equipment, even in the face of global shortages. The UN Compliance Research group will focus during the current cycle on analyzing the compliance of the WHO member states to the organizations guidelines during the COVID-19 pandemic.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.001 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.084 | 0.018 |
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".