Alienating behaviours in separated mothers and fathers in the UK
Bibliographic record
Abstract
Parental Alienating Behaviours (PABs) are the actions taken when one parent tries to harm the relationship between their child and the other parent. This problem is gaining increasing awareness amongst a variety of professionals. To understand it better, we conducted a large survey of over 1,000 separated and/or divorced parents to see how common PABs are and how they impact families. We found that when asked directly, about 39.2% of people said they had experienced PABs. However, when we measured this using specific examples of behaviours, up to 59.1% seemed to have faced PABs. This difference shows that PABs can be hard to identify just by asking people about them, but that they are widespread. We also found that those affected by PABs show greater signs of serious mental stress, like PTSD symptoms, depression, and thoughts of suicide. The way we identify PABs can change these effects, making it crucial to have a full understanding. Participants experiencing PABs also talked about facing more domestic violence, which reflects recent studies from the U.S. and Canada. Considering all this, a two-fold plan is needed. First, we need to boost mental health support by training professionals, creating support groups, and offering counselling to families. It is also key to get schools and the legal system involved. Second, we need to make the public more aware of PABs through large-scale awareness campaigns, which will help society stand against these harmful behaviours. And, of course, we need better research tools to fully understand PABs. In short, PABs are a real and pressing issue. We need a complete response, mixing practical help with improved research.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".