MétaCan
Menu
Back to cohort
Record W7026531707

Alienating behaviours in separated mothers and fathers in the UK

2024· report· en· W7026531707 on OpenAlexaboutno aff

Bibliographic record

VenueInsight (University of Cumbria) · 2024
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHarmVariety (cybernetics)Mental healthPlan (archaeology)Government (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.282
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInsight (University of Cumbria)French-language works237,207