Bibliographic record
Abstract
Understanding young children’s perspectives on their well-being at school is essential to creating environments that best support their development. Well-being is a balance of positive affect, negative affect, and an overall evaluation of life (Diener, 1984). My study seeks to better understand young children’s perspectives on their well-being at school. Participants were 4- to 6-year-old children and their educators from two public schools and one independent school in Ontario. First, I determined whether children’s perspectives of their well-being at school align with those of educators. Children and educators completed a questionnaire – the Multidimensional Life Satisfaction Scale adapted, (MLSS-adapted; Huebner & Gilman, 2002). My analysis of children’s and educators’ perspectives on the questionnaire showed that children’s and educators’ perspectives on children’s well-being at school are different. Then, I further examined children’s perspectives through an open-ended story completion task where children were told the beginning of a story about a character that either has a good dream or a bad dream about school. Children were asked to complete the story by telling about all the good things or bad things that happened to the character. Themes from children’s good dream stories included mentions of food, friends, “other social reference” (e.g., children in general), play, and positive feelings. Children’s bad dream stories included mentions of physical or emotional harm, negative feelings, and “other social reference”. Finally, I studied the relationship between children’s story themes and their well-being at school as indicated by their responses on the questionnaire. Play and friends were frequently mentioned by children with higher well-being in good dream stories and a failure to have expectations met were mentioned frequently by children with lower well-being in bad dream stories. My study showed young children have insights into their experiences at school that are different than those of their educators. By using measures that consider children’s developmental abilities, young children can meaningfully participate in research. Children’s unique perspectives can be used to shape schools and curriculum that best support children’s 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".