‘Guardian Angels’: Essential work, conjunctural crises, and shifting sovereignty in COVID Quebec
Bibliographic record
Abstract
This article critically examines the making of the ‘Guardian Angels’ program, a Canadian special immigration program for Asylum claimants working on the frontlines of the COVID-19 pandemic. The program was the product of community organizing and mediatized ‘essential worker’ discourse which resulted in contest over the terms of migrant inclusion. These debates were waged by migrant justice organizers, who called for “Status for All”, and the Federal and Quebec provincial governments each with their own plans. At first proposed as wide-spanning amnesty for migrant healthcare workers, the Guardian Angels program’s final form was restrictive and exclusionary. Based on our ethnographic work with Montreal’s Immigrant Workers Center, we analyze the program’s logics through a conjectural framework, centering the debates around two overlapping crises: First, the Trump-era rise in asylum-claimant land-border crossings at Roxham Road, and second, the pandemic public health crisis. These moments were seized on by Quebec Premier François Legault’s nationalist CAQ party to increase provincial immigration sovereignty in Canada’s federated immigration framework. We contend these goals were pushed through by bordering through the mechanism of status, a power which we argue is continuous with a broader assertion of territorial control that operates through selection powers.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.023 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".