Are we in this Together? Post‐Separation Co‐Parenting of Fathers with and without a History of Domestic Violence
Bibliographic record
Abstract
This paper explores features of post‐separation co‐parenting from fathers' perspectives in men with and without a history of domestic violence (DV). Co‐parenting interview data from 20 fathers were randomly selected from a larger, longitudinal study (Fathers and Kids) conducted in Toronto, Canada, examining how domestically violent fathers impact children's development. Using thematic analysis, three themes were created for separated fathers without a history of DV: I value my ex‐partner's involvement with our child; we're good as co‐parents; and how we co‐parent impacts our child. Two themes were created for DV fathers: my ex‐partner is a bad mother; and my ex‐partner is responsible for our difficulties co‐parenting. These themes indicate markedly different perspectives between the two groups, specifically in valuing versus disparaging their ex‐partner, cooperation versus blame, and recognition versus no recognition of the potential impact of ongoing co‐parenting conflict on children. The nature of the differences between groups highlights the need to assess and support fathers with a history of DV as co‐parents, and indicates possible targets of intervention for fathering programmes. ‘Explores features of post‐separation co‐parenting from fathers' perspectives in men with and without a history of domestic violence’ Key Practitioner Messages For most fathers with a history of DV perpetration, co‐parenting problems persisted post‐separation. Narratives of most DV fathers demonstrated overwhelmingly negative evaluations of ex‐partners, predominant patterns of blaming mothers for difficulties and lack of insight into the impact of co‐parenting conflict on children. Decisions about the involvement of DV fathers post‐separation should be preceded by thorough and ongoing assessment and, for those with ongoing contact, support in order to safely and effectively co‐parent.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".