The Cruel and Astonishing Tale of Imogen Cabral Da Gama
Bibliographic record
Abstract
This is a novel that takes place primarily in 1947 – 1948—the immediate postwar period—in a fictional British Caribbean island named St. Francis. St. Francis, while a distinct fictional space, is strongly based off the island I grew up in, the Commonwealth of Dominica, in the days after the War when many British Caribbean islands still had American bases and were embroiled in battles to end their rule by the British. The novel follows four primary characters: a teenage trans girl named Imogen, who doesn't even know the word "transgender" might exist and who most of the world knows as "Derek"; her grandmother, Isabel Catarina da Gama, who for many years has lived alone with Imogen in the da Gama family mansion; Beija-flor, a Brazilian teenage girl from Sao Paulo who has come with her father to St. Francis, as her father is involved in a mysterious job in the island, and who has been promised to be married to a man back in Brazil she does not love; and Monsignor Bakkus, a highly influential religious figure in the island who has a secret history with Isabel Catarina that torments him. In the beginning of the novel, the da Gamas' house burns down when Imogen steps outside to investigate two things she isn't accustomed to: the sound of someone singing and the smell of guavas. When she returns, the house is on fire, and her grandmother, furious, tells her Imogen must pay her back for what she has done, as well as to rebuild the house. In order to generate money, the grandmother forces Imogen to put on a disturbing, dangerous show that attracts people from across the island, including American soldiers from the nearby WWII base and the local pastor, who condemns the show and calls the monsignor to the village to investigate. Imogen meets Beija-flor through the show, and the two form a fast friendship. But when Imogen begins to stray beyond her grandmother's control to spend more time with Beija-flor and to try to figure out her own identity, they begin to learn things about themselves and the world that they can never unlearn. When the monsignor arrives in the village with an agenda to not only stop the show and deal with the American soldiers' brothel but to confront his past with Isabel Catarina, chaos ensues, and everyone learns that they must make decisions that will terrify them—and change them forever. This is a novel about love, loss, gender, religion, imperialism, and much more.
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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 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".