<i>Inns of Court</i> . Ed. by A <scp>lan</scp> H. N <scp>elson</scp> and J <scp>ohn</scp> R. E <scp>lliott</scp> , J <scp>r</scp> . <i>Inns of Court</i> . Ed. by NelsonAlan H. and ElliottJohn R.Jr. <scp>i</scp> : <i>The Records</i> ; <scp>ii</scp> : <i>Appendixes</i> ; <scp>iii</scp> : <i>Translations Endnotes Glossaries Indexes</i> . (Records of Early English Drama, 23.) Cambridge: D. S. Brewer; Toronto: University of Toronto. 2010. 3 vols (xcix + 1064 pp). £195. <scp>isbn</scp> 978 1 84384 259 0.
Bibliographic record
Abstract
The twenty-third volume of the REED series is devoted to the documentary evidence of drama and other communal entertainment given at the four Inns of Court and two Inns of Chancery (Furnival's and Clifford's). Like The Percy Papers, therefore, this volume is not devoted to a county but in this case to a body of law societies. It is also unique in that the bulk of the research was conducted by John R. Elliott, Jr, and augmented and completed by Alan H. Nelson after Elliott's untimely death. Such a task would have been very difficult for most, but Professor Nelson was well-placed having been the editor of the Cambridge volume, and being involved in the completion of the Oxford volume, as well as being a close friend of Professor Elliott, who was well-organized and meticulous in his work. Professor Elliott started his research for the Inns of Court in 1988–89, and this volume is dedicated to him.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.499 | 0.341 |
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".