Domestic violence and its relation to dentistry: a call for change in Canadian dental practice.
Bibliographic record
Abstract
Domestic violence (DV), now a national health concern, has pervasive effects at both the individual and societal levels. Women are the primary victims of DV; their lifetime prevalence has been reported to be 20%-53.8%. The sequelae of violence include increased acute and chronic health care utilization, psychological harm and a wide range of physical injuries. Head and neck injuries are the most common result of violence, and many women seek dental treatment following abuse. Dentists are in a unique position to identify abused victims and intervene. However, they are not well trained to identify victims of DV, and they lack appropriate resources to manage identified victims. Moreover, of the many health professionals surveyed, dentists feel the least responsible for intervening in cases of DV, and interventions by dentists are minimal. Barriers to screening for DV occur at the patient, provider and system levels, but they can be overcome with increased education. DV education, assessment and management should be a priority, so that dentists can help improve the lives of the many women faced with abuse.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| 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".