Moral panic about “covidiots” in Canadian newspaper coverage of COVID-19
Bibliographic record
Abstract
Moral panics are moments of intense and widespread public concern about a specific group, whose behaviour is deemed a moral threat to the collective. We examined public health guidelines in the first months of the COVID-19 pandemic in Canadian newspaper editorials, columns and letters to the editor, to evaluate how perceived threats to public interests were expressed and amplified through claims-making processes. Normalization of infection control behaviours has led to a moral panic about lack of compliance with preventive measures, which is expressed in opinion discourse. Following public health guidelines was construed as a moral imperative and a civic duty, while those who failed to comply with these guidelines were stigmatized, shamed as "covidiots," and discursively constructed as a threat to public health and moral order. Unlike other moral panics in which there is social consensus about what needs to be done, Canadian commentators presented a variety of possible solutions, opening a debate around infection surveillance, privacy, trust, and punishment. Public health communication messaging needs to be clear, to both facilitate compliance and provide the material conditions necessary to promote infection prevention behaviour, and reduce the stigmatization of certain groups and hostile reactions towards them.
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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 | 0.009 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 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".