Frankenstein’s Singular Events: Inductive Reasoning, Narrative Technique, and Generic Classification
Bibliographic record
Abstract
In this essay, I suggest that the central section of Mary Shelley’s Frankenstein – the creature’s description of his first experiences – echoes Hume’s and Bacon’s discussions of inductive reasoning. Because the creature must learn the causes of phenomena the reader takes for granted, his story defamiliarizes both the reader’s world and the process of induction itself. The creature’s tale thus functions as a travel narrative, and produces the cognitive estrangement associated with science fiction. I then examine the prominence of inductive reasoning in the novel as a whole, and discuss Victor’s and the creature’s singular situations as resistant to inductive understanding. I argue that Shelley uses various narrative techniques (such as embedded narratives and character doubling) to invite and frustrate readers’ attempts to use induction to solve the novel’s central moral questions. The reader’s inability to form coherent inductive patterns in part accounts for the novel’s radical ambiguity. Finally, I suggest some consequences for Frankenstein ’s relation to the gothic: the novel departs from gothic conventions in its unusual use of the doppelgänger, and its rhetorical goals in invoking induction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".