Prioritizing Vaccine Access for Vulnerable but Stigmatized Groups
Bibliographic record
Abstract
This article discusses the prioritization of scarce and in-demand influenza vaccines during a pandemic. The mass vaccination campaign in Canada against H1N1 influenza in 2009 illustrated that some groups considered vulnerable may also be stigmatized. In 2009, prisoners and people with severe obesity were given priority of H1N1 vaccination in some Canadian jurisdictions. Assigning priority for vaccination to such groups may be socially unpopular. This article examines a number of possible arguments that might motivate opposition to prioritizing stigmatized groups. We find these arguments flawed. They rely on a suspect ‘social worth’ rationale for the prioritization of scarce resources. Furthermore, human rights concerns support the prioritization of vulnerable but stigmatized groups for vaccination during a pandemic. We also argue that it is necessary to prioritize vulnerable but stigmatized groups to promote the common good in its various forms. The article concludes with an analysis of an objection that no vulnerable groups—stigmatized or otherwise—should be given priority for influenza vaccination in a pandemic. We argue that the objection is based on a confusion.
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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 | 0.024 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".