Bibliographic record
Abstract
While family law is not a unique subject matter for research, it is however, a much neglected area. \nWhat sets this work apart, is the significant volume of cases observed and analysed in the Circuit \nCourt, in all 8 Circuits. Information was extrapolated to definitively answer the questions, that to date \nhave been informed by anecdotal conjecture. The effects of a deep recession during the court research \nperiod, October 2008 to February 2012, highlighted the serious failings of an opaque and costly \nsystem, with long delays and over-burdened lists, which resulted in particularly poor outcomes for \nchildren, male litigants and lay litigants. \nWhile case reporting is not in itself an innovation, the development of a large database resource is. \nFor the first time, comprehensive empirical data has been gathered, from 1,087 cases observed during \nthe period of the research. This statistically significant sample size, gives confidence levels of \nbetween +/-3% and +/-0.6%, indicating that the findings are good indicators of what happended \nacross all courts during the research period. \nJudicial interviews were carried out, which assisted with the examination of the decision making of \nthe court, on judicial separation and divorce. While it was expected that inconsistencies would be \nevident from court to court, what was unexpected, was the difficulty in identifying consistencies. \nComparative international research carried out in New Zealand, Canada and America, indicated that \nhearing the views of the child is a priority for most courts. However, a finding in the Irish family \ncourts is the absolute disconnect between the courts and children, who have no voice. This research \nunequivocally shows we are utterly failing the vulnerable members of our society, post the breakdown \nof the ‘family’; particularly children, by refusing to hear their voices, or offer appropriate \nsupport, in matters that are central to their lives.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".