An examination of the self-perceptions of at-risk youth and their educators on competency measures of self-determination
Bibliographic record
Abstract
Abstract This study examines self-determination skills and opportunities among a group of at-risk youth in a Montreal-based alternative school program. Students and their educators were given questionnaires measuring skills on self-determination that addressed choice making, decision making, problem- solving, goal setting, and self-advocacy. Thirty-five students (15-18 years) transitioning from a Montreal area alternative school program to community settings participated in this study. This study documented important differences on the perceptions of students and educators on self-appraisals of capacity and opportunity for self-determination, with students rating themselves higher on capacity than their educators. Results indicated variability among the at-risk groups and educators for opportunities to practice self-determination. Factors such as self-reported learning difficulties/emotional and behavioural disturbances, and levels of stress were found to differentially influence ratings of self-determination. In the context of high stress the majority of our sample experienced multiple risk factors that crossed domains (home and school environments) implicating their school performance. These results have implications for curricula and policies that support self-determination, and they highlight the importance of home-school collaborations
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".