Intern utprøving av CAPE & PAC ved Beitostølen Helsesportsenter
Bibliographic record
Abstract
ABSTRACT\n\nBackground\nThis is a study of two Canadian instruments called CAPE “Children`s Assessment of Participation and Enjoyment” and PAC “Preferences for Activities of Children”. Our purpose was not to gain external validation, but to look at positive and negative aspects of these instruments by exploring the benefits of using them in clinical work at Beitostølen Helsesportsenter (BHSS).\n\nMaterial and method\nWe used both these instruments on six children who where at a habilitation stay at BHSS. Our informants were both boys and girls with different diagnosis, ranging from 7 to 18 years old. The information we got from this research was systematically analyzed and used to get more knowledge about the benefits of these instruments in clinical work.\n\nResults and Conclusion\nBoth instruments were easy to use and understand for the children and for us as interviewers. By using CAPE we got almost a complete picture of the children’s leisure activities. The challenge is that the “interview based” method requires a lot of time. The “self- administered” method will probably require less time, but since we have not explored this method, we don’t know if it would give us the same results as the “interviewed based” method. PAC gives us knowledge about the children’s preferations for leisure activities. It is important that children participate in leisure activities based on their own interests. This will increase their motivation and sense of coping. These instruments can give interesting and valuable information that can be useful in the clinical work at BHSS. The instruments are not translated to Norwegian, and there are several cultural and lingual barriers to cross before the instruments are ready to be used in clinical work in Norway.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.105 | 0.016 |
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".