Eating at the Buffet of Love: “Consummating” <i>Tony n’ Tina’s Wedding</i> in Vancouver
Bibliographic record
Abstract
Food and the communal consumption and enjoyment of food are a focal point of Italian wedding receptions in North America as in Italy (Harney 265), but food and eating take centre stage only briefly in Hoarse Raven Theatre’s Vancouver production of Tony n’ Tina’s Wedding. Vinnie Black, the caterer character, introduces the wedding feast, his “Buffet of Love,” with silly pomp: accompanied by dramatic music from 2001: A Space Odyssey, Vinnie lopes through the reception hall wrapped in an Italian flag and waving a plastic light-sabre toy and effuses into the microphone about how the buffet food has been lovingly prepared. But the fanfare quickly dies down. Even as the first table of audience members queues to load its plates with pasta, chicken, and salads, the antic, diffuse plot of Tony n’ Tina’s Wedding continues to unfold. The food, in its comforting abundance, quietly gives up the spotlight.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".