The Missing Voice: A Comparison of Autistic Adults and Inclusive Employers Perspectives of Work Readiness Skills Needed to Enter the Calgarian Workforce
Bibliographic record
Abstract
This study investigated autistics’ and inclusive employers’ perspectives of work readiness, and how to improve work readiness for those on the autism spectrum. In a qualitative design, eight semi-structured interviews were conducted with employers and autistics from Calgary, Alberta. Interviews were transcribed and data were analyzed via reflexive thematic analysis. Four themes arose from the autistic viewpoint: (1) Holistic perspective of work readiness; (2) Work readiness is not a static concept; (3) Work readiness consists of position-dependent skills; and (4) Increasing work readiness for autistic individuals. Additionally, four themes resulted from the employer viewpoint: (1) Work readiness includes a holistic view of the person; (2) Work readiness consists of the same standards with adjustments; (3) Work readiness consists of position-dependent skills; and (4) Improving work readiness for autistic individuals. The present study has implications for stakeholder viewpoints on work readiness, informing improvements to work readiness programs, and improving employment outcomes for autistic individuals. Implications for practice and future research directions are discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".