Personal and contextual variables predict music consumption during the first COVID-19 lockdown in Canada
Bibliographic record
Abstract
The global COVID-19 lockdowns shattered familiar routines, plunging individuals into a disorienting emotional landscape characterized by loss, uncertainty, and a deep yearning for social bonds. Many employed coping strategies such as cleaning, dancing, and mindfulness-based practices to ameliorate negative emotions. Music listening was one of the most widely used coping strategies, moderated by personal and contextual variables. We obtained data from a Canadian national survey conducted in April 2020 to examine the role of personal (sex, age, education level, pre-pandemic income, minority status, feelings about music, and Schwartz's "personal values") and contextual variables (level of worry, changes to income, COVID-19 status and risk, having children at home, and internet access) in predicting music listening for stress relief, changes to music listening, changes to music watching, and music discovery. Our results indicate that women, younger adults, individuals who like or love music, and those reporting high levels of worry were more likely to listen to music to relieve stress. Personal variables were more significantly associated with music listening for stress relief than contextual variables.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".