Breaking Isolation: Social Work in Solidarity with Migrant Workers through and beyond COVID-19
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
In the early months of COVID-19's proliferation through Canadian communities, the now largely documented uneven impacts and burdens of the illness were emerging. Among the early COVID-19 casualties were workers in Alberta's meatpacking plants, with infection rates so high that the news quickly gained international attention. The Cargill meatpacking plant, overwhelmingly staffed by temporary foreign workers with no permanent status or citizenship rights, was the site of the largest single coronavirus outbreak in Canada. The need for a community response to this emerging crisis was a focal discussion for a newly formed network of social workers. A multileveled series of actions and systems advocacy were put in place. These actions would foment a vibrant and diverse "community of communities" while also unveiling challenges and obstacles to the work during a period of a shifting health landscape, shutdowns, and changing legislation. This article focuses on the development of a grassroots and transformative community-led response to COVID-19, describing strategies, implementation, and challenges in the "real life" context of the recent pandemic. Key learnings for postpandemic community organizing and social work solidarity actions are highlighted.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.007 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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