From solitude to solicitation: How people with intellectual disability or autism spectrum disorder use the internet
Bibliographic record
Abstract
Very little is known about how people with intellectual disability (ID) or autism spectrum disorder (ASD) use the Internet. However, we do know that many of them have limited social circles. Electronic social media could facilitate the development of relationships, increase social participation and reduce social isolation for these people. However it may also expose users to unwanted encounters. Our exploratory study attempts to get a glimpse of Internet experiences of young adults with ID or ASD. Eight participants (five with ID and three with ASD) whose mean age was 25 years participated in this preliminary study. A sociodemographic and Internet use questionnaire was administered with the help of the participants’ support worker. Seven participants agreed to be interviewed by one of the researchers in a separate meeting, in the presence of their support worker. Results show that all participants enjoyed using the Internet for communicating (e.g. Facebook, e‑mail, chatrooms, dating sites) or entertainment (e.g. watching videos, listening to music). Three male subjects played games online, and only participants with ASD (without ID) created content (e.g. website or blog). All interviewees with ID and two of the three with ASD had distressing experiences including: being insulted online, having false rumors spread, receiving threats or being targets of sexual cyber-solicitation. Users with ID have had to rely on friends, parents or social workers to avoid or rectify cyber-victimization episodes. Internet access has opened a wide window of opportunity for people with ID and ASD, but more education and support is needed to ensure safe and positive Internet use by this population.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".