Serving Calgary Men across the Prevention Continuum: Interview Results
Bibliographic record
Abstract
With the highly-visible movements such as #MeToo and #TimesUp there has been increased attention on the role men can play in violence prevention. Locally, we heard from various leaders throughout the violence prevention sector that more men are trying to access local domestic and sexual violence supports and services. Representatives from several agencies and institutions also told us they are experiencing challenges with how to design and offer programs and supports for men, how to create strategies within their organizations to engage and work with men, and how to curate organizational cultures to integrate men into workplaces traditionally dominated by women. In response to these conversations, in 2018, Shift launched a research project to collect information to help identify high-priority and emergent service/capacity gaps related to men’s violence prevention needs with the hope of mobilizing government and community partners to more effectively address these gaps here in Calgary, Alberta. More specifically, the goal of the research project was to better understand who is seeking services, what are these men asking for, and how can the human service sector develop or enhance services to better support their needs while furthering the goal of violence prevention. From June to July 2018, Shift undertook a series of interviews with key individuals working in the Calgary domestic and sexual violence sector to better understand these challenges and to identify possible solutions to more effectively support men across the violence prevention continuum (men as victims, perpetrators, allies, leaders and violence disrupters).
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".