Surviving a Pandemic: The Adaptability and Sustainability of Nonprofit Organizations through COVID-19
Bibliographic record
Abstract
Like many other organizations in Canada and globally, nonprofit organizations have not been insulated from the negative effects of the COVID-19 pandemic. It has affected Canadian nonprofit organizations in numerous ways. This ranges from the effects of COVID-19 on the health of workers and clients to its effect on revenue. As predominantly essential service providers, nonprofit organizations have to find ways to continue operations during the COVID-19 pandemic to ensure that no one is left to fall through the cracks in an uncertain economy. RÉSUMÉ Comme bien d’autres organismes au Canada et dans le monde, les organismes sans but lucratif (OSBL) n’ont pas été épargnés par la pandémie du COVID-19. En effet, pour les OSBL canadiens, celle-ci a eu des incidences dans divers secteurs, allant de la santé des clients et employés jusqu’au revenu. Les OSBL, comme ils sont à toutes fins pratiques des fournisseurs de services essentiels, doivent trouver le moyen de continuer à fonctionner pendant la pandémie afin de s’assurer que personne ne soit oublié dans un contexte économique incertain.
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How this classification was reachedexpand
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".