The Romantic Landscape: A Search for Material and Immaterial Truths through Scientific and Spiritual Representations of Nature
Bibliographic record
Abstract
Landscapes generally bring to mind images of mountains, meadows, and beaches. These images are usually associated in the mind with the beauty of nature. To many, an encounter with nature is an encounter with the divine. While landscapes may evoke notions of nature’s beauty or divine mystery, this link is not always recognized consciously. The association derives from a practiced experience instilled by history and culture, particularly through the pictorialization of nature. Landscape imagery has been a significant part of the history of Western civilization but it was most celebrated during the age of Romanticism. While the distinction between art, faith, and science is part of our contemporary world, this segregation did not always exist. To the contrary, it was the interdependency between art, faith, and science in Romantic landscapes that shapes our perceptions of landscapes today. Subjectivity was pertinent to Romanticism, as the modern desire for authenticity and truth emerged from the regimentation of the Enlightenment. Religious faith was one way for the Romantics to obtain truth, particularly, a divine truth found in nature and art. The representation of sublime landscapes allowed Romantic artists to express their own interpretations of truth. Simultaneously, Romantic science provided alternative narratives for the wonders of the world and the truths of nature. Science influenced the perception of nature and the way it was represented. Artistic depictions of plant-life, geology, atmosphere, and the celestial moon show this connection. However, for the Romantics, it was not only landscapes that embodied the tripartite of science, art, and faith. The meaning of life was dependent on the search for revelation in the material and spiritual worlds. Landscape was a vehicle that allowed for this revelation.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.043 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".