Governing Dogs: An Autoethnographic Tale of Redefining 'Service Dog' in Canada
Bibliographic record
Abstract
Service dogs are becoming an integral part of our society. Consequently, there is a need for research that explores how Canada should proceed with the development and implementation of appropriate laws and policies that will ensure the proper use and equal integration of service dogs. Before this can take place, the terminology used within the field must be clarified, as society continues to move toward a more expanded definition of service dog, and public access challenges continue to impact the lives of persons with disabilities. The goal of this autoethnographical research study was to determine what service dog handlers, particularly ‘owner-trainers,’ feel constitutes a ‘service dog’ in Canada. When researchers conduct investigations on topics related to the lives of persons with disabilities, their research typically takes the form of disabled individuals being studied and not being directly involved within the research. Therefore, this project sought to directly involve persons with disabilities, while also attempting to avoid the possibility of censorship or silence. Through the use of statements from social media, this project captured the lived experiences without worrying about participants changing them to fit within society’s expectations. Society is not structured to be accessible for all, so when ‘accommodations’ are made, it is ‘expected’ that persons with disabilities will show gratitude and not voice their true feelings. Through the use of autoethnography, I shared my experiences, as a service dog raiser, trainer and handler, and provided a glimpse into the lives of other service dog handlers as they participate within their communities. In doing this, I hope the findings of my project will offer an important perspective to the discussion surrounding what constitutes a ‘service dog’ in Canada.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.039 | 0.028 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".