Bibliographic record
Abstract
irector Catherine Rainville intended this production of Measure for Measure to engage with #MeToo and #TimesUp, an intention which is remarkably buoyed by Shakespeare BASH'D's company style.1 According to the program notes, BASH'D puts on "Shakespeare's plays in social settings, creating a relaxed, stimulating environment for the audience."Cofounder and co-artistic director James Wallis explains that this has largely meant "playing Shakespeare in bars," in which the alchemy of informality, intimacy, and alcohol gives the performance the "social, casual atmosphere" of a post-show discussion in a pub. 2 Wallis may be underselling the aesthetic somewhat -Rainville's production is intimate and casual, but also raucous, tense, and bristling with energy.The performance venue is Toronto's Junction City Music Hall, a basement bar in a trendy but away-from-the-downtown-core neighborhood of Toronto.The bar is open throughout, and audience members are encouraged to enjoy a drink during the show.The venue contributes to the production's roughand-ready aesthetic -it's a small, cramped space, with a decent sound system but not much in the way of lighting options, minimal space for a set, and limited options for backstage areas and exits.The primary playing space is a central aisle between two banks of seats, so spectators can see the audience members across from them throughout the performance, weaving our reactions into the show's visual fabric.On the night that I attend, the play is sold out, with audience members filling every booth and stool, as well as the rows of impromptu seating, all doing our best not to spill drinks on one another (or spill one another's drinks).The cramped and rough nature of the space would make an illusionistic performance difficult, if not impossible, and Rainville's production aesthetic turns potential liabilities into strengths by eschewing illusionism in favour of playful theatricality.The costumes are perhaps the purest expression of the production's aesthetic.The show is in modern dress, each outfit exaggerated just slightly so that it straddles the boundary between clothing and costume.Sochi Fried, as Isabella, wears a tight-fitting long-sleeved-and-turtlenecked black shirt and floor-length black skirt, which, combined with a substantial silver cross, evoke rather than replicate a nun's habit.Lesley Robertson's Pompey, in denim vest over black netted shirt conjures a clownish version of working-class street clothes, while Geoffrey Armour's Angelo, in patterned waistcoat, French-cuff dress shirt, and silver tie bar, presents an exaggeration of hipster fastidiousness.These characters are legible as social types as well as layered individuals.The costumes are detailed and deliberate -and often visually striking -but still feel like items that the cast D
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.195 | 0.072 |
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".