TIPPINS AND WITTMANN ASKED THE WRONG QUESTION:. Evaluators May Not be "Experts," But They Can Express Best Interests Opinions
Bibliographic record
Abstract
Tippins and Wittmann (2005) provide an important analysis of the limitations of child custody evaluations, but they are wrong to propose that court-appointed evaluators should be precluded from making recommendations about best interests decisions. While some of the evidence of evaluators may fail to meet the high standard of reliability expected for “expert evidence,” the role of court-appointed evaluators in child-related cases is not the same as the role of party-retained experts in other types of litigation, and the legal basis for their involvement in the family law dispute resolution process is very different. The family courts should not apply the “expert evidence” standard when deciding how to use the evidence of a court-appointed evaluator, but rather should use a more flexible standard that takes account of the family law context. If the Tippins and Wittmann proposal is adopted, it will have negative implications for the resolution of family law cases, including making settlements less common, thereby deleteriously affecting children.
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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 | 0.019 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.026 | 0.023 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".