Kitchen Sink Realisms: Domestic Labor, Dining, and Drama in American Theatre by Dorothy Chansky (Review)
Bibliographic record
Abstract
The October 2008 issue of Theatre Journal was bookended by articles from Jill Dolan and Dorothy Chansky that separately reevaluated two stalwarts of the second-wave feminist movement: Wendy Wasserstein (Dolan) and Betty Friedan (Chansky). Together, they marked one unofficial beginning of what has since become a vibrant contemporary movement (including my work with Roberta Barker in Canada, as well as work by Elaine Aston in the United Kingdom, and Varun Begley and Cary Mazer in the United States) to rethink, reframe, and reclaim stage realism in all of its fraught complexity. While it is impossible to recuperate stage realism naively, thanks to the robust critique leveled against it by feminist and critical race scholars over the past four decades, it is—as the above writers contend—nevertheless necessary to parse that critique with care, to distinguish among the multiple practices and strategies (dramaturgical, technical, and performative) that constitute the thing(s) we mean when we talk about “realism,” and to take the measure of the different kinds of cultural work that multiple “realisms” can do—sometimes separately, sometimes in tandem, and sometimes at tantalizing cross-purposes with one another.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".