Evaluation of Community Veterinary Outreach (CVO) One Health Clinics in Vancouver, British Columbia, Canada
Bibliographic record
Abstract
In Canada, it is estimated that 20% of people are experiencing housing insecurity and homelessness are pet owners. It has been reported that the bond between companion animals and this population is typically stronger than the general population. This bond is associated with numerous health benefits and can act as a motivator for changes in healthy behavior, yet vulnerably housed pet owners also experience increased barriers to accessing healthcare services for both themselves and their pets. The registered charity Community Veterinary Outreach (CVO) has the mandate to mitigate these structural and socioeconomical barriers by coordinating and delivering “One Health” clinics in the community. One Health clinics offer integrated veterinary and human health services, which aim to improve public health and build on the health benefits of this human-animal relationship. CVO has been operating in Vancouver, British Columbia, Canada since 2016, and anecdotal data demonstrates the success of the program. However, to date, no formal program evaluation has been completed for Vancouver’s One Health clinics. The aim of this project was to evaluate the CVO Vancouver One Health Clinics and its capacity to connect marginalized community members to healthcare services and promote public health, through the use of the CDC Program Evaluation Framework. Findings from this study demonstrate that CVO Vancouver One Health Clinics achieve their short, intermediate, and long term outcomes by promoting access to care and improving the health of vulnerably housed people and their pets.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".