Development of a direct observation Measure of Environmental Qualities of Activity Settings
Bibliographic record
Abstract
AIM: The aim of this study was to develop an observer-rated measure of aesthetic, physical, social, and opportunity-related qualities of leisure activity settings for young people (with or without disabilities). METHOD: Eighty questionnaires were completed by sets of raters who independently rated 22 community/home activity settings. The scales of the 32-item Measure of Environmental Qualities of Activity Settings (MEQAS; Opportunities for Social Activities, Opportunities for Physical Activities, Pleasant Physical Environment, Opportunities for Choice, Opportunities for Personal Growth, and Opportunities to Interact with Adults) were determined using principal components analyses. Test-retest reliability was determined for eight activity settings, rated twice (4-6wk interval) by a trained rater. RESULTS: The factor structure accounted for 80% of the variance. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.73. Cronbach's alphas for the scales ranged from 0.76 to 0.96, and interrater reliabilities (ICCs) ranged from 0.60 to 0.93. Test-retest reliabilities ranged from 0.70 to 0.90. INTERPRETATION: Results suggest that the MEQAS has a sound factor structure and preliminary evidence of internal consistency, interrater, and test-retest reliability. The MEQAS is the first observer-completed measure of environmental qualities of activity settings. The MEQAS allows researchers to assess comprehensively qualities and affordances of activity settings, and can be used to design and assess environmental qualities of programs for young people.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".