"Shocking his readers out of their complacence": gothic and fantasy tropes in H.G. Wells' «fin-de siècle» science fiction novels.
Bibliographic record
Abstract
The main goal of this thesis is to identify Gothic and fantasy tropes in four fin-de-siècle novels by H.G. Wells – The War of the Worlds, The Invisible Man, The First Men in the Moon and The Food of the Gods – and to examine their rhetorical effects within the framework of science fiction. More precisely, my project was inspired by Kelly Hurley's analysis of the thematic similarities shared by the science fiction and Gothic genres during the fin-de-siècle, and by Darko Suvin's definitions of science fiction and of the Gothic as being rhetorically antithetical. Through an analysis of how the two thematically compatible but rhetorically antithetical genres interact in the novels, I evaluate the potential responses that could be expected from readers, and compare these responses to the contemporary reception of the work. My research is based on the idea that Wells' novels promote a social message based on Darwinian theory and socialism, and that he uses the combination of SF and the Gothic in order to lead his complacent readers to intellectual conclusions by first drawing their attention through shock and terror. This study will seek to determine whether the author's use of the Gothic ultimately benefits the works by enhancing their social message, or if it results in the contrary effect.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".