[학술논문] Simulations of America in Mark Twain's Extract from Captain Stormfield's Visit to Heaven
Bibliographic record
Abstract
Mark Twain's pessimism in his late years has been irrefutable orthodox for his biographical environment. He had gone through severe business flasco for "the collapse of his publishing house and the failure of the Paige typesetting machine" and several deaths in his family, including his first daughter Susy's death in August 1896 and his beloved wife Olivia's in June 1904, both of whom were muse to him (Skandera Trombly 7). He later works were consequently interpreted under the umbrella of pessimism. Extract from Captain Stormfield's Visit to Heaven(1909) was not an exception. This travelogue has been interpreted as the expression of his satiric skepticism about "human vanity and conventional religious beliefs about heaven and the afterlife." The French philosopher Jean Baudrillard's simulation theory in his Simulacra and Simulations(1981), however, overturns such a dystopian interpretation, Baudrillard's concept of simulation illuminates that Twain undermines the conventional concept of America by simulating it. Its intertextual reading in juxtaposition with Canadian novelist Margaret Atwood's Surfacing(1972) reveals that Twain's simulation of America embodies his deconstructive-reconstructive blueprint for his homeland. Baudrillard's utopian vision of America presented in his travelogue, America(1986), reinforces the subversive pleasure of disclosing Twain's hopeful frontier spirit.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".