Bibliographic record
Abstract
Allistic actors have long portrayed autistic characters on-screen -a topic of critique for autistic advocates (Jones, 2022).Cue As We See It: a 2022 Amazon Original series about three autistic roommates navigating their twenties.The series intentionally cast autistic actors and addresses a demographic of autistic people often overlooked in television: the youth precariat (Aspler, Harding, & Cascio, 2022).This research explores whether and how As We See It adds complexity to discussions around work and disability/autism.Applying Fairclough's Critical Discourse Analysis, I examine the show's pilot episode and reception among key audiences.Several themes emerged reinforcing an ableist/neurotypical discourse that valorizes ideal bodies and minds within a capitalist order, around which autistic people are disciplined.An alternative discourse also emerged celebrating autistic pride.This study contributes to the developing field of Critical Autism Studies and explores the affordances of a critical, materialist approach in furthering questions of autistic labor.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.032 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".