TOWARD THE DIFFERENTIATION OF HIGH‐CONFLICT FAMILIES: AN ANALYSIS OF SOCIAL SCIENCE RESEARCH AND CANADIAN CASE LAW
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social science research and the courts have begun to recognize the special challenges posed by “high‐conflict” separations for children and the justice system. The use of “high conflict” terminology by social science researchers and the courts has increased dramatically over the past decade. This is an important development, but the term is often used vaguely and to characterize very different types of cases. An analysis of Canadian case law reveals that some judges are starting to differentiate between various degrees and types of high conflict. Often this judicial differentiation is implicit and occurs without full articulation of the factors that are taken into account in applying different remedies. There is a need for the development of more refined, explicit analytical concepts for the identification and differentiation of various types of high conflict cases. Empirically driven social science research can assist mental health professionals, lawyers and the courts in better understanding these cases and providing the most appropriate interventions. As a tentative scheme for differentiating cases, we propose distinguishing between high conflict cases where there is: (1) poor communication; (2) domestic violence; and (3) alienation. Further, there must be a differentiation between cases where one parent is a primary instigator for the conflict or abuse, and those where both parents bear significant responsibility.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it