stratification to compare their treatment of thought through geological images. In addit...
Bibliographic record
Abstract
Abstract: Strata and Sediment under the Fog focuses on geological landscapes and how they are a stand-in for the mind’s landscape. This article looks at how American artist Robert Smithson describes the mind through geological landscapes in his writings and how Canadian artist Paterson Ewen diagrammatically represents the organization of rocks. The work of these two artists is considered according to the philosophies of Gilles Deleuze and Immanuel Kant—two philosophers who rely on geological and geographical models and metaphors to communicate the function of thought. Robert Smithson’s drawings of grand scale Earth-works and Paterson Ewen’s paintings of colossal earthly phenomena consider the landscape from a geological perspective. In Smithson’s art, geology is a stand-in for the topography of the mind. Ewen, for his part, sees in geological structures a matrix of organizational processes. Both artists create geological landscapes to communicate a spatial image of the mind which brings their artistic endeavours on to the plane of a particular philosophical programme. When philosophers attempt to sketch out the landscape of the mind, they resort to a rhetorical constellation associated with geography and, more precisely for the purpose at hand, geology, in order to communicate a spatial image of thought. Geology allows both artists and philosophers to produce an illustration of thought that puts the emphasis on the notion of
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".