Anti-Intellectualism and the Mass Public’s Response to the Covid-19 Pandemic
Bibliographic record
Abstract
Anti-intellectualism – the generalized distrust of experts and intellectuals – is an important concept in explaining the public’s engagement with advice from scientists and experts. We ask whether it has shaped the mass public’s response to COVID-19. We provide evidence of a consistent connection between anti-intellectualism and COVID-19 risk perceptions, social distancing, mask usage, misperceptions, and information acquisition using a representative survey of 27,615 Canadians conducted from March to July 2020. We exploit a panel-component of our design (N=4,910) to strongly link anti-intellectualism and within-respondent change in mask usage. Finally, we provide experimental evidence of anti-intellectualism’s importance in information search behaviour with two conjoint studies (N~2,500) that show respondents’ preferences for COVID-19 news and COVID-19 information from experts dissipate among those with higher levels of anti-intellectual sentiment. Anti-intellectualism poses a fundamental challenge in maintaining and increasing public compliance with expert-guided COVID-19 health directives.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".