‘I get to learn more stuff’ : children’s understanding of wellbeing at school in Winnipeg, Manitoba, Canada
Bibliographic record
Abstract
This purpose of this study was to explore how school-aged children understand dimensions of wellbeing in a Canadian context in participation of the Multi-national Qualitative Study – Children’s Understanding of Wellbeing. Twenty-one school-aged children (boys = 8, girls = 13) participated in semi-instructed interviews facilitated by tactile, tasked oriented interview tool. Participants were recruited from seven before- and-after-school child-care programs throughout the city of Winnipeg, Manitoba, Canada. The wellbeing of children at school was influenced by the quality of the relationships they had with their teachers. Children recognized teachers as being essential agents in their learning process and teaching them essential skills for their future. Children who described feeling positive about school were children who felt that their teachers were supportive, provided creative ways to learn, and listened to their ideas and concerns. Conversely, children who described negative feelings about school discussed experiencing teachers who did not value their ideas and concerns, and were not supportive in their individual needs as a learner. The teaching style of teachers affect children’s wellbeing at school. Teachers who promote wellbeing at school and positive feeling associated with learning are those who consider the voices and needs of their students, as well as make efforts to incorporate those considerations in their curriculum.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".