Bibliographic record
Abstract
Contemporary Western theatrical productions with themes about and old age often yoke to decline by highlighting narratives of dependency and loss in their live performances. One reason is a tendency to interpret scripts through the lens of chronological time, a sense of time that defines age solely in terms of number of years lived, and creates rigid expectations about life-stages. Recognizing the limitations of the life-stage model, postmodern theorists, building on Judith Butler’s discourse on gender, have considered age in terms of its performativity and looked to theatre as a way to study this. Such discourses dismiss the idea that involves embodiment of time because, in postmodern tradition, they do not want to understand time as simply progressive and linear. However, some age theorists argue that postmodern definitions of age are problematic because they deny the very real effects of time on the body. By contrast, theatre and age studies scholar Anne Davis Basting insists that there can still be a postmodern poetics of the body that acknowledges its temporal component. In this article, Julia Henderson uses Basting’s depth model of aging to analyze age-effects in a Vancouver production of Shakespeare’s King Lear by Honest Fishmonger’s Equity Co-op. Through a close reading of the actors’ embodied performances and her affective response to them, Henderson argues that Basting’s model reveals how the contemporary production of a classical work can engage with postmodern concepts of time while still considering age. In doing so, the production highlights more positive age narratives rather than reinforcing a narrative of decline. Henderson extends Basting’s model by drawing connections with Marvin Carlson’s theory of theatrical ghosting, suggesting that reception of theatrical performances of age is not only influenced by layering of memories of past performances of age on stage, but also by a kind of anticipatory quality engendered by the process, which she terms a ghosting forward. Connecting these theories offers a way to differentiate between performances of age without relying on a chronological sense of time or restoring age binaries. Henderson’s analysis contributes to the rather new body of research at the intersection of age studies and Canadian theatre studies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".