Embracing Neurodivergence: Essential considerations in family law practice
Bibliographic record
Abstract
Abstract Neurodiversity encompasses the natural wiring of the mind, shaping how individuals think, behave, communicate, and perceive the world. While society largely caters to the neurotypical majority, neurodivergent individuals, who represent a minority, experience the world differently and face unique challenges. Stigma persists surrounding neurodivergent people, and they are consistently marginalized. Family law professionals often work with neurodivergent individuals but need improved awareness and knowledge of neurodivergent traits and client presentation. Recognizing neurodivergence and providing inclusive support and access to services is crucial. This article defines relevant concepts and definitions and provides scenarios and examples that illustrate how neurodivergence may show up in day‐to‐day family law practice. Tips are provided for increasing awareness for professionals, along with practical suggestions for working with neurodivergent individuals.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".