At Both Ends of the Leash: Preventing Service-Dog Oppression Through the Practice of Dyadic-Belonging
Bibliographic record
Abstract
There is a growing interest in the “use” of service-dogs to enable persons living with disability to navigate the world more independently in North American culture. While this may appear to be progress, the question remains, for whom? Although there is evidence that the presence of a service-dog is beneficial for persons living with a variety of disabilities, this trend is not devoid of embedded assumptions and a related need for caution. How persons living with disability and nonhuman animals, in this case dogs, are treated both matter equally. One set of needs stemming from structural oppression must not eclipse another’s set of needs. The “use” of one party in order to emancipate another, is therefore fraught with necessary cautions. There are shared oppressions and rights at both ends of the service dog leash.
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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 | 0.027 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.036 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".