How to Do Nothing with Words, or <i>Waiting for Godot</i> as Performativity
Bibliographic record
Abstract
This essay analyzes how Waiting for Godot exposes the structural logic of both rhetorical and dramatic performativity. Drawing on the languagephilosophy of J.L. Austin and Ludwig Wittgenstein, Richard Begam considers what happens to ‘‘performative’’ locutions – statements that actually make things happen, such as ‘‘I now pronounce you man and wife’’ – when they are theatrically represented. Austin claims that such locutions when uttered on stage are rendered intransitive – i.e., they lose their performative force – and are therefore relegated to the Kantian realm of the purely aesthetic. Yet Beckett’s play spends two acts demonstrating that the primary function of language is not ‘‘constative’’ – not meant to give us a picture or representation of reality. Rather, Beckett’s conception of language – drawn from his reading of Mauthner – is essentially performative. But if words, phrases, and sentences all function performatively, if all descriptive uses of language are, in fact, instrumental uses, then the larger effect is to return illocutionary or transitive force to the theatre. As a result, Beckett’s play breaks through the wall not only of Ibsenian realism but also of Kantian aestheticism, reclaiming for the dramatic event the kind of ‘‘there-ness’’ that Alain Robbe-Grillet discovered in the first performances of Godot.
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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 | 0.002 |
| 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 | 0.030 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".