Bibliographic record
Abstract
Many of the discussions with my fellow contributors to this Forum aptly identify ways in which liberal arts education in general, and theatre and drama curricula within the liberal arts in particular, are already providing university undergraduates with skills they will need for successful lives and careers in the twenty-first century. I’m more than happy to embrace the idea that our programs and departments should be better recognized by administrators and the public for the things we already do well. I would nevertheless advocate at least one important curricular reform that might be made to many of our programs in drama and theatre studies: dramaturgy, in the many places where it is not already the case, should be made part of the core of any university education in theatre and drama. Making this practice as integral to our curricula as courses in acting, directing, or design will not only help to prepare our students for the professional careers in the theatre that a small number of them will have, but will also provide invaluable skills for navigating a culture in which information technologies have left us all on the precipice of fundamental shifts in how we work, live, and come together to create political communities.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.006 |
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".