Topografía y alegoresis en El primer loco , de Rosalía de Castro
Bibliographic record
Abstract
This article deals with the last of the novels written by Rosalía de Castro, El primer loco [The first inmate] (1881). From the perspective of a critical literary geography, it proposes an analysis of the referential logic that organizes this significant novel, which is very close in its conception and publication to En las orillas del Sar [On the banks of the river Sar], the last of the author’s great collections of poetry. The article specifically tackles the web of meanings underlying the choice of the key settings of the novel, Santiago de Compostela and the neighboring monastery of Conxo, both of which underwent processes of change related to deep ideological, social, but also spatial transformations that were current at the moment of the novel’s writing. These locations are conceived as products of discursive practices—produced places—allowing us to attend to them in terms of intertextual convergences and tensions among seemingly distant media like fiction, guidebooks, art history or painting and photography. Against this background, this article suggests a new interpretation of this often neglected work, which should be revised in the context of the Galician and Hispanic literature of the last quarter of the nineteenth century.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".