The Experiences of Mothering with an Intimate Partner Violence-related Brain Injury
Bibliographic record
Abstract
One in three Canadian women will experience intimate partner violence (IPV) in their lifetime, and 75% of them have a probable brain injury (BI) (Haag et al., 2022). Despite the recent growth of IPV-BI research, many survivors remain undiagnosed and many aspects remain unexplored. The experiences of being a mother with an IPV-related BI has been left untold. These gaps leave frontline workers with little guidance in supporting survivors who are specifically mothers. This research reports on a qualitative study exploring the lived experiences of mothering with an IPV-BI. The study uses a constructivist worldview and hermeneutic phenomenology to amplify mothers' voices and provide examples that challenge deficit models of parenting within IPV contexts. The findings highlight mothers’ strength, self perception, and mothering roles in the context of their IPV-BI. As mothers who have experienced IPV-BI are often judged and questioned, changing how we view their mothering capacity is vital. Findings highlight these demands of parenting, and how societal pressures of what it means to be a ‘good mother’ place pressure on many women. Especially with the added factor of a BI, survivors’ sense of self as a mother is impacted. Recommendations for policy and practice provide insight into these nuanced discussions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".