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
Once constituted, scientific facts have a way of roaming about on their own in the world, much divorced from the circumstances of their original constitution. An important part of Latour and Woolgar's discussion in Laboratory Life was to draw attention to how facts are used once they are at the final stage of their constitution. What I propose to do here is to go one step further, and to follow a single fact around in the wild—to tag it, as it were, much as a biologist might tag an animal with a radio collar—and then look to see where it turns up. The fact I have chosen is especially taggable, simply because it happens to be fantastic: I refer to the fact that magnets will lose their power of attraction if they are rubbed with garlic. This fact is also useful because it shows up in authors spanning fifteen centuries, from Plutarch through Rabelais and beyond, and over this time it shows some interesting behaviors. Of course, in the end, the garlic-magnet antipathy was disproved, and so changed its epistemological status, moving from one extreme to the other: from the obviously true to the obviously ridiculous. What struck Rabe-
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 | 0.000 | 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 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| 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