Understanding the experiences of autistic high school students and neurodivergent job coaches in a summer employment program: an interpretive description study
Bibliographic record
Abstract
PURPOSE: This study explores the experiences of autistic youth and neurodivergent job coaches during a job training program. METHODS: Interpretive Description methodology guided this study. Two researchers facilitated virtual focus groups with autistic students and neurodivergent job coaches separately before (n = 14) and after (n = 12) the program. Thematic analysis was conducted to identify codes and develop themes. RESULTS: Seven themes were developed, which included both autistic high school students and neurodivergent job coaches' perspectives about JTP: JTP surprised students; unexpected experience of working, students experienced a sense of community support in transitioning to work, students built rapport with neurodivergent job coaches, neurodivergent job coaches were buffers to students, building trusting connection; neurodivergent job coaches' interactions with students, unexpected reality and a sense of community in coaching autistic students, and neurodivergent job coaches' personal growth and the evolving role of coaching. CONCLUSION: The findings of this study suggest that positive work experiences and relationships between neurodivergent job coaches and students occurred within a specific program that recommended clear communication about expectations, roles, and support preferences. The findings can guide future community partnerships to promote workplace participation and facilitate accommodations based on the needs of neurodivergent population, including autistic individuals.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| 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".