Passing on the Torch of Learning in the 'Primordial Soup' of Construction Law: Reflections from the Construction Law Academic Forum, 2012
Bibliographic record
Abstract
The focus for the session was upon two key themes: fostering the growth of construction law as an area of study; and bridging disciplinary gaps by teaching construction law to, and learning from, students from disciplines other than law.The Forum was chaired by Matthew Bell of Melbourne Law School, with discussion led by a distinguished panel comprising: Oscar Aitken (Carey y Cia, Santiago), Professor Ian Bailey SC (Professorial Fellow, Melbourne Law School; Wentworth Chambers, Sydney), Professor Philip Britton (Senior Fellow, Melbourne Law School and Former Director, Centre of Construction Law and Dispute Resolution, King’s College London), Philip Bruner (Founding Fellow and Past President, American College of Construction Lawyers; JAMS, New York), Associate Professor Philip Chan (National University of Singapore), Professor Philip Evans (Murdoch University School of Law), Associate Professor Paula Gerber (Monash University Law School), Professor Doug Jones AO (Professorial Fellow, Melbourne Law School; Clayton Utz, Sydney and Atkin Chambers, London), Dr Arthur McInnis (Professional Consultant, Chinese University of Hong Kong), Professor Rashda Rana (Adjunct Professor, Sydney Law School; Atkin Chambers, London and Ground Floor Wentworth Chambers, Sydney), Bruce Reynolds (Founding Governor and Past President, Canadian College of Construction Lawyers; Borden Ladner Gervais, Toronto).
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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.054 | 0.033 |
| Scholarly communication | 0.029 | 0.017 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.020 | 0.033 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".