Domestic Violence Screening Education and Implementation in Nursing Station in Northern Manitoba
Bibliographic record
Abstract
Domestic violence (DV) has been around for many years. Today and for the last several decades, it had become increasingly known as a large social problem. This project gave the nurses working in the federal nursing stations of isolated northern Manitoba information and education on DV. The aim of this project was to improve the nurses' ability to screen, detect, communicate, support, and refer victims ofDV to the appropriate resources. This project was based on two parts: an education package and a telephone conference that took place with the nursing stations . The education package consisted of a variety of information DV, such as: risk factors, prevalence, the cycle of violence, types ofDV, health effects, legal implications for reporting and documenting in the province of Manitoba, the Abuse Assessment Screening Tool, an algorithm, a resource directory, and an internet resource list. These topics were included in that package to give the nurses an overview ofDV, information on screening, and to help refer the victims of DV to the appropriate resources . An educational package was sent out to each of the nursing station. The nurses working in the isolated federal nursing stations were the population/group participating in the telephone conference. Consent and evaluations forms were sent out with the education package. Participation was voluntary and anonymous. No compensation was provided for the participants. The duration of the telephone conference was approximately 45 minutes. The results of this project were restricted by the limited participation. Out of a possible 75 nurses that could have attended, 14 nurses participated and only 5 evaluations were returned. The education packages are in the nursing stations and will remain there . Even though only 14 nurses participated, all nurses may use this package. This project is a step in the continued education of nurses on DV. As the nurses working in northern Manitoba are working with a population at high risk for DV, it is important that they be aware of this issue and how to deal with DV when it arises in their practice
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".