The COVID-19 Pandemic: Key Factors in Canada’s Social Policy Development
Bibliographic record
Abstract
Many studies focus on the COVID-19 pandemic, response mechanisms and response design. At the same time, it becomes more and more obvious that not only the study of economic policy and decisions made by the government in connection with the pandemic is acquiring relevance. As the spread of the disease continues, social problems and difficulties that political elites will have to deal with are exposed in Canadian society. Despite the fact that the government has taken unprecedented measures to expand assistance and social protection to the most vulnerable groups – low-income families, women, senior citizens, young people and children, low-skilled workers, self-employed, people with disabilities, etc. – the pandemic, however, has had a profound impact on society. The government will be forced to adapt its policies in the field of social protection and labor relations, in the field of health and education. This article seeks to explore the key social dimensions of the COVID-19 pandemic, as well as factors that can influence the political decisions of the Canadian elite in the near future.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".