Harriet Beecher Stowe’s Uncle Tom’s Cabin
Bibliographic record
Abstract
1852 Introduction: Harriet Beecher Stowe (1811–1896) was born in Litchfield, Connecticut. She was the daughter of Lyman Beecher, a Presbyterian minister who was also a temperance advocate and an abolitionist. Her husband, Calvin Ellis Stowe, was a theologian who taught at a seminary. The Stowes were strongly opposed to slavery and helped runaway slaves find their way to Canada through the Underground Railroad. In 1850 Harriet Beecher Stowe began writing fictional articles for the magazine National Era about the life of a slave, Uncle Tom, and his family. The story begins with a Kentucky plantation owner, Arthur Shelby, having to sell a slave, Uncle Tom, to pay debts. Below is a small selection from the novel focused on Aunt Chloe, an excellent cook who is Uncle Tom’s wife. Aunt Chloe proposes to the Shelbys that she be rented out to raise money so she can buy back Uncle Tom, who has been sold to a barbarous man, Simon Legree. Aunt Chloe will earn enough money to buy back Uncle Tom, but by then he is dying. These articles were collected into a two-volume novel, Uncle Tom’s Cabin, that was published in 1852. A play based on the book was released the following year. The book sold more copies than did any book other than the Bible. Uncle Tom’s Cabin galvanized the North in opposition to slavery and angered many in the South. Some observers have claimed that Uncle Tom’s Cabin was a contributing factor in causing the Civil War.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.006 |
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".