Passport to neoliberal normality? A critical exploration of COVID-19 vaccine passports.
Bibliographic record
Abstract
Throughout the COVID-19 pandemic governments across the world including in France, Canada, Lithuania, Austria, Italy, and Ireland imposed ‘vaccine passports’ on the premise that they would curtail transmission of the virus, reduce COVID-19 related mortalities, and enable society to return to neoliberal normality. However, vaccine passports raise several important and troubling issues that have not been given sufficient attention within the social sciences. Therefore, this article offers a critique of vaccine passports. It is structured into three key themes: (a) scientifically and ethically problematic, (b) the death of the social and the ‘Other’, and (c) digital surveillance and freedom. The article begins by exploring how vaccine passports make little scientific sense and further entrench some unvaccinated peoples’ sense of political and medical mistrust. It then discusses how they amplify social divisions, creating the unvaccinated Other in society and intensifying the neoliberal shift towards a post-social, contactless world. The paper closes with an outline of how vaccine passports were cast as enabling a return to neoliberal normality and freedom, hinging upon an assumption of harmlessness while cementing the negative ideology of capitalist realism.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.136 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".