Het besluitvormingsproces van civiele rechters in procedures over de gevolgen van een (echt)scheiding met een beschuldiging van seksueel kindermisbruik
Bibliographic record
Abstract
Allegations of child sexual abuse during divorce proceedings and custody and access disputes: the decision-making process of civil judges This study aims to provide insight into allegations of child sexual abuse in the context of divorce, and related, proceedings by analyzing the decision-making process of civil judges. To this aim, interviews with 13 judges and 11 lawyers were conducted and a focus group was organized with different specialists. It is concluded that in the eyes of the judges, allegations of child sexual abuse in this context are not rare, and some of the professionals signal an increase of allegations in the last decade. The presence of an allegation poses a dual issue: it points out problems within the family, as well as causes problems for the child. This dual nature makes it even more complex for judges to make decisions, especially concerning contact between father and child. The validity of the allegation becomes less important than its presence when judges consider the children’s best interests. The judges’ aim to create conditions for the family within which the child’s safety is best protected, can as an unwanted consequence delay the process, which in itself can be damaging for the child.
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 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 | 0.033 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 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".