“It Could Be Worse … It Could Be Raining”: The Language of Meteorology in Shelley’s Frankenstein and Its Intersemiotic Translations
Bibliographic record
Abstract
The language relating to climatic conditions certainly plays a major role in the novel Frankenstein, published by Mary Shelley in 1818. The aim of this article is therefore to analyze the use the author makes of this language, which often acquires symbolic overtones that work in synergy with the development of the plot and the characters’ psychology, and study the way this same language is adapted and exploited in some of the films that translate the novel intersemiotically. To this end, this paper will focus on the cinematographic adaptations of Shelley’s work dating from 1931, 1994 and 2015, although sporadic references to other products will be made too. During the analysis, some of the notions of intersemiotic translation will be applied to the selected corpus, in order to demonstrate how the practice of various forms of translation, including inter- and intra-semiotic translation, heavily contributes to the creation of the canon we live by.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".