Autistic sociality: challenging representations of autism and human-animal interactions
Bibliographic record
Abstract
PURPOSE: The objective of this synthesis research was to explore representations of autism and human-animal interactions (HAI) in the health sciences literature and the implications for autistic children and their families. METHODS: Guided by critical interpretive synthesis methods proposed by Dixon-Woods et al. (2006), we synthesized and examined how autism and HAI were described in the health sciences literature and explored assumptions and goals underlying HAI as an intervention. RESULTS: Across 47 reviewed articles, animals were represented as therapeutic objects whose purpose from a biomedical perspective was to address "problematic" behaviours and "deficits" in social functioning and development. HAI was employed as a therapy to address improvements in these problematic behaviours in the majority of studies. Relational and social aspects of HAI were present but not explicitly discussed. An alternative perspective proposed by Olga Solomon positioned autistic sociality as one form of diverse human socialities that can be embraced, rather than held problematic and in need of being normalized. CONCLUSIONS: Implications for HAI in rehabilitation include recognizing the multiple purposes of animals in a child's life, not only the therapeutic goal of normalizing functioning.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".