Challenges Encountered by 17 Autistic Young Adults in Hong Kong
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The self‐portrayals of 17 young persons with autism spectrum disorder reveal the challenges encountered by them, including study problems, inter‐personal relationships, being bullied by classmates at school, discrimination by the public in general and teachers, social workers, and peers in particular, obstacles to post‐secondary education, difficulties in securing and maintaining employment, psychological distress, and so on. This may indicate ineffective inclusive education and practice even though the government has injected a significant quantity of resources to implement inclusive education in Hong Kong. Clearly, more can be done by the government to help them overcome these challenges, especially regarding the issues of bullying at school and transition from school to work. Of course, the subjective self‐portrayals of youngsters on the spectrum in limited numbers can never allow us to view the whole picture. However, the book opens up a means for us to better understand them. Hopefully, it can trigger more concerns from the public, especially the government officials, and more research from scholars in Hong Kong.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it