Lockdown and Children’s Well-Being: Experiences of Children in Switzerland, Canada and Estonia
Bibliographic record
Abstract
Abstract This paper addresses the well-being of children in Switzerland, Canada and Estonia, as they experienced the lockdown imposed by governments after the state of international public health emergency, declared by the World Health Organization on 30 January 2020. Suspension of school or starting with distance learning, cessation of extracurricular activities, closure of playgrounds, parks, shopping centres and loss of daily contacts with friends completely transformed children’s lives. The surveys conducted by the authors in individual ways, were all inspired by their membership to the Children’s Understandings of Well-Being network and involved the participation of 403 children aged 7–17 years old (229 girls and 174 boys). They present the emerging trends from the children’s narratives focusing on their experience of the lockdown in relation to family life, school life, contacts with friends, and in relation to space, time and self. During the lockdown leisure activities and hobbies, followed by life with friends and school life challenged relational well-being the most, while family life opened up new perspectives and generational solidarity. Staying at home and decreased physical activity impacted on the physical health of children, missing direct contacts with friends and teachers put social relations to test, fear of the virus decreased feeling safe and secure, and the lockdown restricted participation in society. The findings underline the relational nature of their well-being. More in-depth studies are needed to highlight the widening of inequalities and the balance between protection and participation of children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".