Hunted to Extinction: Finding Lost Species in the World of Bernard Palissy (1510–89)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Contrary to the idea that awareness of extinction is quintessentially modern, this article argues that Bernard Palissy conceived of extinct species—what he called “lost species” (“espèces perdues”)—in the sixteenth century. This premodern craftsman knew that human activity caused species to vanish. But how? By retracing his interactions with merchants and fishermen at the French Atlantic ports, I show that Palissy learned about the overfishing of waters from other commercial actors. Rather than paint human-caused extinction as a novel insight, I demonstrate that Palissy drew on common vernacular knowledge about the depletion of the ocean. Palissy's pronouncements, it is further shown, expand his well-known polemic against bookish learning. The artisan championed practical experience against a textual tradition of natural history, exposing the latter's silence on commercially decimated species.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it