The Improvising Judge: An Interview with Her Honour Judge Patricia Smyth, Northern Ireland County Court
Bibliographic record
Abstract
Her Honour Judge Patricia Smyth (HHJ Smyth) was interviewed on Wednesday 22 June 2016 at the Newry Courthouse, Northern Ireland, by barrister Seamus Mulholland and legal academic Sara Ramshaw. HHJ Smyth was an invaluable contributor to the Into the Key of Law research project, volunteering as a project interviewee, focus group member and a panel participant at the “Just Improvisation: Enriching child protection law through musical techniques, discourses and pedagogies” Symposium at Queen’s University Belfast, 29 – 30 May 2015. In this interview, HHJ Smyth provides valuable insight into a variety of important issues, such as training judges to become better improvisers, the limits of improvisation in, particularly, Northern Irish family law, the existing structures or skills that make improvisation possible and, perhaps most importantly, the importance of creativity, “bespoke solutions”, and attentive or deep listening in the family law realm.
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 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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.012 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.020 |
| Insufficient payload (model declined to judge) | 0.008 | 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".