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
In most everyday instances of reasoning, reasoners can gain, lose, and reacquire entitlement to (or justification for) a possible commitment (or belief) as a result of their consecutively acquiring new commitments. For example, we might initially conclude that ‘Tweety can fly’ from ‘Tweety is a bird,’ but later have to reject this conclusion as a result of our coming to learn that Tweety is a penguin. We could, even later, reacquire entitlement to ‘Tweety can fly’ if we became committed (and presumably entitled) to the claim ‘Tweety has a jetpack.’ I will call this very common feature of reasoning entitlement recovery. In this paper I will argue that the types of inferential relations that are central to Brandom’s entire account of language and reasoning make entitlement recovery impossible. I will then briefly attempt to diagnose why this problem arises for Brandom and suggest how his account should be modified so that it will successfully allow entitlement recovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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