Of elemental forces & compositional forms: recent work by Adam Bobette & Christine Shaw with respondent Etienne Turpin
Bibliographic record
Abstract
This ART PANEL will feature a conversation between the educator and curator Christine Shaw, Ph.D., and the artist and landscape architect Adam Bobbette, whose recent projects engage the problems and ambiguities of the elemental and their attendant forms of composition, in relation to wind and fire, respectively. In both Shaw's curatorial project developed through her engagement with Sir Francis Beaufort's Scale of Wind Force, and Bobbette's project for a guide to the 'Combustible City' of Manhattan, there is an attempt to relate the force of the elemental to the form of composition in the work of curation and artistic practice. The discussion will be moderated by Etienne Turpin, Ph.D., whose recent work also engages themes of the elemental, primarily through his study of the Anthropocene and its legibility in Northern Ontario, Canada. The panel will develop the theme of 'the elemental' as an anticipation of and an analog to the pharmakon through an interrogation of the ambiguities, reversabilities, and elisions that the forces of the elemental make manifest. The goal of this panel is to discuss recent projects by Shaw and Bobbette that signal the strange yet productive force of elemental autoantonymics - those grandparents of the pharmakon - as they relate to current themes in aesthetics, urban ecology, and philosophy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 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".