Bibliographic record
Abstract
Origins of the Gothic novel [W]hatever is fitted in any sort to excite the ideas of pain and danger, that is to say, whatever is in any sort terrible, or conversant with terrible objects, or operates in a manner analogous to terror, is a source of the sublime. It is something for a man to be able to walk from his own door to his place of worship without being shot at from behind his father’s tombstone. After 1757, a large number of novels in English adopted, explored, adapted and perverted the aesthetic theories set out in Edmund Burke's A Philosophical Enquiry into the Origin of our Ideas of the Sublime and Beautiful . They did this through new attention to landscape, through the deployment of historical settings and themes, and through an interest in the sensational and the supernatural. The most obvious influence of Burke's treatise is found in the subgenre of terror fiction that quickly identified itself as Gothic. The sublime is produced by great and terrible objects, including natural phenomena like oceans, mountains and waterfalls, as well as great buildings whose size overwhelms the spectator. Burke emphasises that a certain amount of obscurity is necessary for the creation of terrible effects. To enter a ruined abbey on a moonlit night would be to invite the experience of the sublime. Small and pleasing objects are beautiful, and, in terms of landscape, the beautiful is associated with domesticity and cultivation. Burke leads his readers to associate the sublime with masculinity and the beautiful with femininity.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 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".