Playing it safe? An evolutionary life history theory perspective on Canadian adolescent play during the COVID-19 pandemic
Bibliographic record
Abstract
Playing during adolescence is hypothesized to prepare young people to respond to unexpected future challenges. But, when extrinsic environmental risks are high, adolescents are expected to prioritize immediate-payoff behaviours over playing. It is unclear, though, how an ecological shock like a spike in community spread of a potentially deadly virus might affect adolescent play. Using data from a socio-demographically-diverse sample of 460 Canadian adolescents surveyed across varying levels of threat/restrictions during the COVID-19 pandemic, of whom 39 also engaged in focus groups, we explored variations in time allocations to play. We regressed indicators of respondents' time spent on play on whether they responded during a pandemic wave peak, and on socio-ecological-demographic parameters. Health indicators were then regressed on the play. Focus group quotes and perspectives contextualized the quantitative findings. There was no clear evidence of changes in overall time allocations to play during increased viral threat/restrictions, but modes of play were atypical for adolescents, regardless of when they responded. Adolescents living under more stressful socio-ecological conditions engaged in less play. The play was positively associated with health indicators. Pandemic spikes did not reduce the time Canadian adolescents spent playing, but likely affected how they played, which has implications for their current and future well-being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".