On the Contrary: Inferential Analysis and Ontological Assumptions of the A Contrario Argument
Why this work is in the frame
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Bibliographic record
Abstract
We remark that the A Contrario Argument is an ambiguous technique of justification of judicial decisions. We distinguish two uses and versions of it, strong and weak, taking as example the normative sentence “Underprivileged citizens are permitted to apply for State benefit”. According to the strong version, only underprivileged citizens are permitted to apply for State benefit, so stateless persons are not. According to the weak, the law does not regulate the position of underprivileged stateless persons in this respect. We propose an inferential analysis of the two uses along the lines of the scorekeeping practice as described by Robert Brandom, and try to point out what are the ontological assumptions of the two. We conclude that the strong version is justified if and only if there is a relevant incompatibility between the regulated subject and the present case.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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