Imagine Canadas Sector Monitor: Ongoing Effects of the COVID-19 Pandemic
Bibliographic record
Abstract
Nearly a year into the global COVID-19 pandemic, Canada's charitable sector has been at the forefront of providing supporting and vital services to people in need. In the early days of the pandemic, Imagine Canada sought to better understand how lockdowns, cancelled events, the need for immediate digital adaptations etc. were impacting the ability of organizations to fulfill their missions.This second Sector Monitor report, focused on the health and well-being of the country's charities, was commissioned to take the pulse of how organizations and leaders were faring. In particular, we sought to track the ripple effects of the global pandemic and its impact on the ability of organizations to continue to deliver services.With over 1,000 organizations reporting, we are confident that this snapshot accurately reflects the 'on the ground' reality that is being experienced. We have been able to better understand the changes in demand for services, the softening of revenue streams, the impact of federal government support measures and the impact to staff well-being.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".