An Instagram Content Analysis: Investigating the Autisticats
Bibliographic record
Abstract
This study is a content analysis of the Instagram group The Autisticats. The group creates posts regarding autistic experiences by autistic people. It is a public group that has created a learning and sharing community between autistic and non-autistic people. A literature review investigating how autism has been shaped by society yielded themes regarding norms, intervention, culture, and community. This study identifies and analyzes the dominant autistic narratives and counternarratives proposed by the Autisticats and how these narratives shape autistic experiences. The Autisticats have created a space for autistic voices to be heard, and this research is intended to amplify the group’s reach by highlighting their counternarratives. This study identified themes and counternarrative such as, autistic behaviours are human behaviours, treatment versus support, advocacy and reframing autism. The themes were presented to followers in various types of posts such as, informational, opinion, personal experiences, multimodality, and calls to action.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".