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 Logical rationalism asserts that we can acquire immediate, non-inferential justification for beliefs in basic logical principles. The intuitions that arise when we consider particular cases of validity can offer justification for our foundational logical beliefs about rules of inference. I motivate rationalism through an argument from the indispensability of intuitions. This argument shows that rationalism is the theory best equipped to solve the problem of background logic. This is the challenge of explaining how we gain justified beliefs in rules of inference without using those rules in a viciously circular way to arrive at the beliefs. As rationalism is the best epistemology which solves this important challenge, it is our best account of logical knowledge. In addition, I argue that a second major motivation for logical rationalism arises from work on logical practice. Recently, it has been claimed that we should attend to the practices of logicians when selecting an epistemology of logic. I argue that these considerations from logical practice also favour the adoption of logical rationalism.
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 | 0.001 | 0.001 |
| 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 | 0.001 | 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