Imagine Canadas Sector Monitor: Ongoing Effects of the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it