LMDA Review, volume 11, issue 1
Bibliographic record
Abstract
Contents include: Advocacy Guidelines,LMDA Members Meet with the NEA, Update The Elliot Hayes Award,Update Script Exchange, Presentation Of Elliott Hayes Award to Rebecca Rugg, To Lynn Thomson, Conference Panels and Sessions, Conversations About Digital Dramaturgy, Key Note, Dramaturg As Generator, Multi-Authorship: Too Many Cooks?, Desperately Seeking Research, On Copyright, The Dramaturg As Advocate For The Arts On City, State/Provincial, And National Levels, Entrances And Exits, The (New Play) Workshop's The Thing, Anne Cattaneo On Commissioning New Work, LMDA Regions And VPs, News From Canada, News from Baltimore, News from Chicago, The Past Two Years, and On, Notes to Fellow LMDA Members, Spotlight on Early Career Dramturgs, Dramaturgy Opening Arena Stage, Internship at the Women's Project, Literary Residency in New York, Dramaturgy/Literary Management Internship at Arena Stage, Job Opening at UCSD, A Note to LMDA Members, Unity Fest 2001 Call for Scripts, Call for Directors, Actors, Dramaturgs, and Call for Updates to the LMDA Guide to Programs in Dramaturgy.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.075 | 0.028 |
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".