Undergraduate Student Perceptions of Service Dog Teams in Academic Settings
Bibliographic record
Abstract
The presence of service dogs (SDogs) on university campuses has grown in recent years, particularly those assisting individuals (i.e., handlers) with invisible (e.g., psychiatric) disabilities. Handler accounts suggest that disability visibility can influence social treatment of SDog teams (handler + SDog); however, the role of disability stigma in shaping social responses remains unclear, particularly in post-secondary settings. The existing literature has not sufficiently explored whether undergraduate students' perceptions of SDog teams in academic settings differ based on the handler's disability type. The present study sought to answer the following research questions: (1) How do undergraduate students perceive peers who are assisted by SDogs in post-secondary settings, and (2) do undergraduate student attitudes and supportive behaviours differ based on the handler’s perceived disability type? If so, how? Using a between-subjects design, 135 undergraduate students (Mage = 21.10) were randomly assigned a hypothetical scenario describing a peer assisted for their disability by a distinct SDog subtype (i.e., mobility support dog, medical-alert dog, or psychiatric SDog) in a classroom setting. Descriptive analyses showed low perceived disability responsibility, neutral to positive affective reactions, and generally supportive behavioural intentions towards SDog teams. ANOVA results revealed no statistically significant differences across conditions. Results indicate that participants generally perceived SDog teams positively, regardless of the handler’s disability type. Such findings have positive implications for undergraduate SDog teams and suggest that stigma surrounding psychiatric disabilities is low or diminishing, at least among students. A future replication study with a broader sample of Canadian students is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".