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Het besluitvormingsproces van civiele rechters in procedures over de gevolgen van een (echt)scheiding met een beschuldiging van seksueel kindermisbruik

2017· article· en· W2789237171 on OpenAlexaff
Anne E. Smit, Catrien Bijleveld, M.V. Antokolskaia

Bibliographic record

VenueRecht der Werkelijkheid · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsAllegationContext (archaeology)False accusationChild sexual abusePsychologySexual abuseChild abuseSocial psychologyCriminologyLawPolitical sciencePoison controlSuicide preventionMedicineHistory

Abstract

fetched live from OpenAlex

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 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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.000
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 head0.053
GPT teacher head0.377
Teacher spread0.324 · 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 designNot applicable
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

Citations1
Published2017
Admission routes1
Has abstractyes

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