Toward a Progressive Ethics of Shamelessness: Heresy and Affect in Bernard Shaw’s <i>Saint Joan</i>
Bibliographic record
Abstract
In popular discourse, shamelessness is generally used as a negative term, tending to denote narcissistic behaviour that destroys the social fabric. Contrary to this tendency, in illustrating the relationship between heresy and affect in Saint Joan (1923), Bernard Shaw provides the template for a progressive ethics of shamelessness. While he is often considered a creator of puppets that merely voice his ideas, this article argues that his characters contend with complex emotions and that he is attuned to the ways in which affect governs human relationships and political institutions. Through Joan’s refusal to be ashamed of her heresies – her proto-Protestantism, her proto-feminism, and her proto-nationalism – Shaw makes a compelling case for shamelessness as having the potential to impel society toward positive evolutionary change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".