Review: A Publication of LMDA, the Literary Managers and Dramaturgs of the Americas, volume 17, issue 1
Bibliographic record
Abstract
Contents include: Editor's Page: A Note from New LMDA President, Brian Quirt; Think Dramaturgically, Act Locally! A Conference Overview; I Was Mugged at My First LMDA Conference; First-Timer Fragments; Conference Photos; Introducing the Lessing (and Joe and Michael); A Message Faxed from Romania; Acceptance Speech, Michael Lupu; Producing The Belle's Stratagem; Dramaturging Justice: The Exonerated Project at the Alley Theatre; Past President Liz Engeleman: Some Appreciations; The Toronto Mini-Conference (reprinted from the LMDA Canada newsletter); Gateway to the Americas, The LMDA Delegation, A Report from Mexico; Imag[in]ing Poverty: Creative Critical Dramaturgy for Suzan-Lori Parks's In the Blood; Hester, La Negrita in Iowa City, Staging "Spells" and Homelessness in Suzan-Lori Parks's In the Blood; The Future of Theatre is...(a creative contest); Seventh Annual Call for LMDA Residency Proposals.\nIssue editors: D.J. Hopkins, Madeleine Oldham, Carlenne Lacosta
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.046 | 0.020 |
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".