COVID-19 and the Restructuring Collective Solidarity: The Case of Volunteer Activity in Québec
Bibliographic record
Abstract
Drawing on a combination of survey data, semi-structured interviews, and document analysis, this article explores the main forms of restructuring that have taken place within Québec’s voluntary sector in response to the COVID-19 pandemic. It centres on three main shifts: the designation of certain voluntary activities as “essential services” by politicians; the im- plementation of new approaches to soliciting, matching, and retaining volunteers; and the institutionalization of a new health-centric rationality within the supervision of volunteer work. The article concludes by calling for recognition, in theory and practice, of the essential role that volunteering plays with regard to socio-territorial resilience. RÉSUMÉ Mobilisant les données d’un travail de veille portant sur l’impact de la pandémie de COVID-19 sur le secteur de bienfai- sance au Québec, cet article explore les principales restructurations qui se sont opérées au sein du secteur bénévole. Nos enquêtes nous ont permis d’en dégager trois : la qualification, par le politique, de certaines activités bénévoles en « services essentiels » ; la mise en œuvre de nouvelles approches en matière de sollicitation, de jumelage et de rétention des bénévoles ; l’obligation pour les organismes d’encadrer le travail des bénévoles en fonction d’une « rationalité sanitaire ». L’article se clore avec une discussion où nous appelons à reconnaître, tant en théorie qu’en pratique, le rôle incontournable du bénévolat en matière de résilience socio-territoriale.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".