Bibliographic record
Abstract
This phenomenological study explored the lived health experiences of seven children with physical disabilities and associated secondary conditions. The children, between 9-13 years, attended the same elementary school. Semi-structured interviews were conducted with the children. Child experiences were sought through a scrapbook interviewing technique where photographs were utilized as prompts to enhance participant recall and reflection (Harvey et al., in press). Rich discussions were generated to capture the essence of the health for each child. The children were actively engaged in this visual approach to qualitative research methodology which assisted in the co-construction of their own health reality through a collaborative research process with the primary researcher (Harvey et al., in press; Knowles & Sweetman, 2004; Phoenix, 2010). Thematic analyses were conducted on the verbatim transcriptions of the interviews. Four themes emerged from the data: (a) my scrapbook, (b) what I do during my free time, (c) people around me, and (d) what helps me and what doesn't. The results demonstrated the effectiveness of the unique scrapbook interviewing technique to gain a child-driven understanding of the conception of health. The results also reflected the importance of family members, the leisure activities of the children, and the affordances and constraints that enabled or constrained the children to incorporate healthy behaviors. Data triangulation, member checks, audit trail, peer-review, and researcher reflexivity were used to establish trustworthiness of the children's stories. The children with physical disabilities told positive stories about health that may help to create child-friendly physical activity and health interventions at home, school, and community.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".