Development of a Measure to Assess Youth Self-reported Experiences of Activity Settings (SEAS)
Bibliographic record
Abstract
There is a need for psychometrically sound measures of youth experiences of community/home leisure activity settings. The 22-item Self-Reported Experiences of Activity Settings (SEAS) captures the following experiences of youth with a Grade 3 level of language comprehension or more: Personal Growth, Psychological Engagement, Social Belonging, Meaningful Interactions, and Choice & Control. Forty-five youth aged 14–23 years (10 with severe disabilities) completed the SEAS in 160 leisure activity settings. The SEAS has good to excellent internal consistency (Cronbach’s alpha from 0.71 to 0.88) and moderate test–retest reliability (mean scale intra-class correlation coefficient = 0.68), as expected due to changes in activity settings over time. The SEAS was able to differentiate various types of activity settings and participation partners. The SEAS can be used to gain greater understanding of situation-specific experiences of youth participating in various types of recreation and leisure activity settings, including youth with different types of disabilities and those without disabilities.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".