Bibliographic record
Abstract
Shakespeare’s 17th century The Tempest, written during early British colonial times, tells the story of Prospero, the Duke of Milan, who arrives at an island with his infant daughter and enslaves its Indigenous natives, Caliban and Ariel. The play is an allegory of European colonization and imperialism that both promotes colonization and begins to question it. Cesaire’s A Tempest, written in 1969 and approaching a post-colonial era, takes the political and ethical questions surrounding colonialism even further. These questions in both plays are rooted within the relationship between Caliban, one of the island’s Indigenous natives, and the European settler, Prospero. Though Cesaire’s A Tempest is an adaptation of Shakespeare’s original play, it differs significantly from The Tempest in that Cesaire’s narrative is a post-colonial work and thus presented from the perspective of the native population, represented by the character Caliban, rather than Prospero’s settler perspective which was the focus of Shakespeare’s narrative. This post-colonial perspective alters our understanding of Prospero and Caliban from civilizing settler and savage to abusive colonizer and abused colonized, or master and slave. This power relationship is demonstrated through the two characters’ portrayals in the two plays, their power dynamics, and their use of language as a tool both of colonization and rebellion.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.023 | 0.062 |
| Scholarly communication | 0.022 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".