Bibliographic record
Abstract
Meeting the needs of women survivors of intimate partner violence (IPV), that seek \nemergency shelters across Canada is a persistent concern in shelters across the country as women \nare experiencing high rates of stress-related challenges after feeling abuse such as post-traumatic \nstress (PTSD), anxiety and depression. The annual national report of YWCA Canada \nacknowledges that women’s shelters require innovative, cost-effective supports that use a \ntrauma-informed perspective to meet the diverse needs of their residents. They propose VAW \nshelters collaborate with local and provincial agencies to develop effective solutions and \nimplement best practices that can empower women. My research study explored the suitability \nand effectiveness of an innovative mindfulness-based intervention (MBIs) called the Holistic \nArts-Based Program (HAP) to teach mindfulness skills to women survivors of intimate partner \nviolence (IPV), living in an emergency shelter. Arts-based methods are enjoyable and engaging, \nand enable individuals to express feelings/thoughts that might otherwise be difficult to elicit; this \ninformation is rich and interesting, even powerful. Results of qualitative thematic analysis of preand post-group group interviews led to the development of three main themes: (1) benefits of \nlearning mindfulness skills and concepts, (2) benefits of arts-based experimental methods, and \n(3) benefits of strength-based group work. Participation in HAP helped women survivors \nmitigate the negative impacts of stress, and taught them mindfulness concepts and activities that \nthey were inspired to use in their own lives and introduce them to their children. My research \ndemonstrates how interventions such as the HAP could make a difference in women’s mental \nhealth. As MBIs may not have universal appeal they should not be a mandatory program \nrequirement, but consideration may be given to offer mindfulness interventions to empower \nwomen survivors of IPV in emergency shelters.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.033 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".