Bibliographic record
Abstract
A fifteen-year-old boy decides to accompany his severely depressed high school French teacher on a road trip to the Canadian province of Quebec, where the mother tongue of Voltaire and Balzac is still spoken and cherished. Clarence Coo’s mesmerizing new play is a delicious amalgam of farce and tragedy, a carnival funhouse with very dark corners. Wildly inventive and heartbreakingly sad, the strange odyssey of Jimmy and the unpredictable Mr. Green takes many surprising turns, crossing the border from reality into unreality and back again while encountering displaced characters from history, literature, and the mundane, often dangerous world. Selected by Tony Award–winning playwright John Guare ( House of Blue Leaves, Six Degrees of Separation, and others) from over 1,000 submissions from 29 countries, Clarence Coo’s Beautiful Province is the sixth winner of the DC Horn Foundation/Yale Drama Series Prize. In his foreword, Guare calls Coo’s work “elusive and haunting . . . funny, desperate, insane,” praising it for “its intriguing story [and]its tone, sustained to the very end.” Lyrical and adventurous, Beautiful Province is an outstanding new theatrical work, well deserving of these accolades and more.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".