<i>Ouch</i>! A cross‐sectional study investigating self‐reported human exposure to dog bites in rural and urban households in southern Ontario, Canada
Bibliographic record
Abstract
This study investigated self-reported dog bites in humans in rural and urban households in southern Ontario, Canada. Our objectives were to determine, and compare, the incidence of dog bites in rural and urban households, and to describe the profile of bite victims, biting dogs, and the proportion of biting dogs that respondents self-reported as being not up to date on rabies vaccination. We conducted a cross-sectional observational study using an online questionnaire. The 2,006 respondents, each representing one household, included 1,002 rural and 1,004 urban residences. The incidence risk of at least one person in the household being bitten over the previous year in rural households (6.09% per year) was less than in urban households (10.76% per year). In 53.20% of households from which at least one person had been bitten within the past year, only a single person had been bitten. Mostly, victims were 25 to 34 years old (21.67%), male (54.19%), and playing with or interacting with the biting dog at the time of the incident (59.11%). Most biting dogs were 3 to 5 years old (32.02%), males (53.69%), and unleashed (76.85%). Based on self-reporting by respondents, 83.33% of respondent-owned biting dogs were vaccinated against rabies at the time of the biting incident. Irrespective of dog ownership, the odds of an individual in a rural household being bitten by a dog were 0.53 (95% CI: 0.38-0.73) the odds for an individual in an urban household. Dog bites constitute a serious, yet preventable, public health concern that requires targeted, community-specific efforts. Public health organizations could consider findings in developing messaging, particularly as we highlight biting dogs reported by their owners as not up to date on rabies vaccination.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".