Discourse: A Call to Focus Our "Passion for Substance" on Family Violence
Bibliographic record
Abstract
Why has family violence not been claimed by the Canadian nursing community as a vital issue for practice and research, when violence has affected the health of most Canadian individuals, families, and communities? The prevalence of family violence in Canada is well documented (Canadian Centre for Justice Statistics, 2000; Statistics Canada, 1993), and research supports the fact that family violence is a major health issue with grave consequences for physical, emotional, and social well-being (Butler, 1995; Campbell, 2000; Campbell, Harris, & Lee, 1995). Yet violence is not addressed widely in Canadian nursing education, research, or practice. In this discussion, we explore the conditions that have contributed to this apparent disregard of violence in the Canadian nursing agenda, and the consequences of this neglect for responsive research, theory, policy, and practice. The Canadian Context Canadian geography, history, and politics pose a unique set of challenges for dealing with violence and abuse. The vastness of the country and its relatively sparse population act as barriers to the formation of teams, networks, and a critical mass of researchers and practitioners concerned with violence, and to the provision of adequate services, particularly in rural settings.
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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 | 0.054 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.087 | 0.184 |
| Scholarly communication | 0.035 | 0.041 |
| Open science | 0.009 | 0.030 |
| Research integrity | 0.022 | 0.034 |
| Insufficient payload (model declined to judge) | 0.007 | 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".