Res, veluti per Machinas, Conficiatur: Natural History and the 'Mechanical' Reform of Natural Philosophy
Bibliographic record
Abstract
This paper revisits Bacon's persistent 'mechanical' imagery by which he described the 'aid' through which the human mind would be rendered adequate to framing axioms about nature's processes and properties that underlie all natural phenomena. It argues that the role Bacon ascribed to his own insights into the properties and motions of matter is crucial for grasping such instrumental imagery, because his own writings--both methodological and natural historical--need to be read as themselves comprising, at least in incipient form, the very instruments of which they speak. From that reflexive standpoint, this paper in particular focuses on the 'aid' to the senses that his natural histories were to have offered under the interpretative guidance offered by the Novum organum and other works. The 'hypothetical' status to which Bacon is often thought to have accorded his own natural philosophical insights does not adequately take into account the transformative power Bacon thought these insights should have through his own writings. The fact that Bacon was keenly sensitive to the psychological effects of textual authority in his intellectual milieu prompts new reflection concerning how he intended his own texts to be read, and how we should read them.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".