Bibliographic record
Abstract
Postmodernism, as conceived by literary criticism, has a particular taste for revisions, reconfigurations or reconsiderations of works belonging to a past that continues to haunt us, despite the many layers of interpretation that now mystify it. In a 2016 novel adaptation of William Shakespeare's The Tempest, the much-acclaimed Canadian writer Margaret Atwood reconstructs the original plot of the play, cleverly exploiting its semantic potential for today's audiences. While preserving some of the elements and patterns in Shakespeare's text, the novelist introduces a series of displacements and changes at various levels. One of the most intriguing aspects of Atwood's novel is that it is entitled Hag-Seed (a derogatory term used by Prospero to address Caliban in Shakespeare's play), while there is no clearly identifiable Caliban in it. The present paper explores this puzzle, by pondering on Atwood's narrative techniques of emphasizing and developing certain discreet but unsettling meanings whose seeds are to be traced in Shakespeare's play.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".