Categorizing mothers' and fathers' conceptualizations of children's serious play‐related injuries: “You won't grow a finger back”
Bibliographic record
Abstract
BACKGROUND: There is inconsistency across child development and care literature in operationalizing serious play-related injury and also a lack of understanding of how mothers and fathers conceptualize serious play-related injury. The current study explores parents' perspectives of their 2- to 7-year-old children's serious play-related injuries in urban and rural areas of British Columbia and Québec, Canada, and provides an urban/rural and gender analysis of the results. METHODS: We conducted semistructured interviews with 41 mothers and 63 fathers from 57 families, a total of 104 participants, in urban and rural locations in British Columbia and Québec, Canada. We used a social constructionist approach to the research and reflexive thematic analysis to construct themes from participant responses and to inform the consequent categorizations of serious play-related injury. RESULTS: The results indicate four categories of parents' conceptualizations of serious play-related injury: (a) injury requiring medical intervention, (b) injury resulting in head trauma, (c) injury resulting in debilitation, and (d) broken bones. CONCLUSIONS: Child development and care advocates can use these categories to strengthen their communications with parents and to improve understanding of parents' conceptualizations of children's serious play-related injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".