Bibliographic record
Abstract
This article explores the changing uses of the word landscape over time, using ideas from the philosophy of Michel Serres to examine the word’s relevance to contemporary debates on humans and nature. It begins by reflecting on the three types of domestication of the landscape (the farm, the garden, and the national park) identified in Serres’s introductory essay to a book to commemorate the fortieth anniversary of the Pyrenees National Park. These three figures provide a point of departure for an exploration of how the changing meanings of the word “landscape” in the English language reflect our position as humans with respect to nature. Using the geological metaphor of the stratigraphic column to look at different strata in the word’s history and the different meanings associated with it over time, the first part of the article examines how a specific usage of the word associated with each stratum reflects a certain way of seeing the world and the human position in it. Having thus grounded the term etymologically, the second part of the article examines how ideas from Serres’s The Incandescent embody a fundamental shift in how the human subject is conceived, providing a philosophical foundation for a new way of thinking about landscapes, advocating the importance of the concept for reflecting on the ecological challenges we face in the twenty-first 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".