Kant on Time II: The Law of Evidence of the <b> <i>Critique of Pure Reason</i> </b>
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
Abstract Dieter Henrich’s “Notion of a Deduction” (1989) opened up approaches to both Deductions in terms of legal as opposed to syllogistic reasoning. Since the KrV is shot through with juridical metaphors and analogies, many points of connection suggest themselves. In this paper, I extend and modify Henrich’s approach, in order to extract a particular logic of evidence. I argue that the three syntheses of the A-Deduction correspond to parts of a deductive procedure, and that their names have been chosen to indicate this connection to the reader. Nonetheless, the principal aim of the paper is not to develop and defend these historiographical claims, but to explicate the structure of the logic of evidence in question and link it to Kant’s intended refutation of Hume. Since the procedures Kant describes are part of the law of evidence of many nations and are equally well at work in contemporary information-theory, a precise reconstruction can map directly onto contemporary problems in philosophy, physics, and informatics, without any loss of historical accuracy.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it