What's the experience of getting a service dog in Canada?
Bibliographic record
Abstract
Service dogs (SDs) are increasingly being trained to assist people living with disabilities. Despite this, the Canadian SD industry is unregulated, resulting in standards and practices that may differ widely between organizations. To date, no research has examined these practices, making it unclear as to whether the needs of both handlers and SDs are being adequately met. We investigated the experience of acquiring a SD for Canadians with disabilities. An online anonymous questionnaire was administered to 261 Canadians who currently work or have previously worked with a SD to aid with a disability. To acquire their most recent SD, 34% were given or purchased a fully trained SD from an organization, 19% trained a family pet with the support of an organization, and 14% worked with an organization to receive and train a SD. Most participants (75%) required a referral from a health professional to receive their SD. Over half (59%) of participants did not have to go on a waiting list to receive their newest SD. For those that did, 35% waited less than one year and 37% waited more than 2 years. Most participants (87%) had associated costs for acquiring their SD, which commonly included the cost of the SD itself, veterinarian costs, and training. Over one-third (39%) of participants reported receiving no financial support for training costs. The majority (72%) were either very satisfied or satisfied with their primary organization. This presentation provides insight into the varying experiences of navigating the SD industry in Canada that range in accessibility and cost. These findings identify potential areas of improvement and success for SD providers as well as present the current landscape of the Canadian SD industry for policy makers. We conclude that SD organizations should collect and publish data related to the process of acquiring a SD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".