Normalization and Civility: Attitudes and Trends Around Mask-Wearing among MacEwan Students in Fall 2024
Bibliographic record
Abstract
COVID-19 remains a prominent threat years after its initial sweep across the globe. Despite this, public health measures have fallen to the wayside; vaccine supplies face delays, rapid test kits are difficult to access, and mask-wearing now lacks the attention it received years prior. In this project, I examined current attitudes and trends around mask-wearing among MacEwan University students. Using grounded theory (Starks & Trinidad, 2007), I conducted one focus group with three MacEwan students, and qualitative observations from three different locations at MacEwan University. Mask-wearing on campus has become less common overall, and the mask’s once-salient status as an emotionally and politically charged symbol has lessened compared to previous pandemic years. Further, mask-wearing is not seen as a necessity to maintain public health or an intrusion on one’s autonomy, but as an individual choice for individual protection, adopted only in particular circumstances. As COVID-19 and other health crises continue to threaten our health and well-being, examining current attitudes around mask-wearing and mask mandates can provide direction for further action to mitigate COVID-19 and prevent future pandemics.
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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 | 0.002 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".