Privacy Attitudes and Behaviours of Autistic and Non-Autistic Teenagers on Social Networking Sites
Bibliographic record
Abstract
Researchers postulate that autistic teenagers are more vulnerable to privacy threats on social networking sites (SNS) than the general population. However, there are no studies comparing these users' privacy concerns and protective strategies online with those reported by non-autistic teenagers. Furthermore, researchers have yet to identify possible explanations for autistic teenagers' exceptional risk of online harms. To address these research gaps, we conducted semi-structured interviews with 12 autistic and 16 non-autistic teenagers assessing their privacy attitudes and behaviours on SNS, and factors affecting their privacy. We used videos demonstrating relevant SNS scenarios as prompts to engage participants in conversation. Our thematic analyses demonstrated that autistic participants were more averse to taking risks on SNS than non-autistic participants. Yet, several personal, social, contextual, and SNS design factors made autistic participants exceptionally vulnerable to cyberbullying and social exclusion online. We provide recommendations for making SNS safer and more inclusive for autistic teenagers.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".