Living in autistic bodies: bloggers discuss movement control and arousal regulation
Bibliographic record
Abstract
AIM: We sought to deepen understanding of embodied experiences of autism by examining how autistic bloggers describe and discuss autism. METHODS: Working within a qualitative description approach, we sampled 40 blogs written by people who identify as autistic. We conducted a directed content analysis, applying a codebook that was generated using themes from a previous study, while remaining open to additional theme generation and elimination. RESULTS: The rich description in the blog posts support our previous finding that autism is a highly embodied experience including challenges with movement control. Additionally, we found arousal regulation (ability to maintain a calm yet alert state) to be an important embodied experience for the bloggers. CONCLUSIONS: Our findings support a conceptualization of autism that sees embodiment, movement and arousal regulation as important elements of autism. Rehabilitation researchers and professionals should note that autistic insider perspectives can and must be accessed for optimal outcomes.IMPLICATIONS FOR REHABILITATIONClinicians should consider movement control (starting and stopping movement at will) difficulties as possible barriers to function for some autistic people.Clinicians should consider arousal regulation (ability to govern physiological and psychological activation level) difficulties as a possible barrier to function for some autistic people.Clinicians should be cautious when interpreting observed behaviours of autistic people and should make every effort to get explanations for behaviour directly from the perspective of individual clients.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".