Bibliographic record
Abstract
JM: You've suggested many times that human cognitive capacities have limitations; they must have, because they're biologically based. You've also suggested that one could investigate those limitations . NC: in principle. JM: . . . in principle. Unlike Kant, you're not going to simply exclude that kind of study. He seems to have thought that it's beyond the capacity of human beings to define the limits . . . NC: . . . well, it might be beyond a human capacity; but that's just another empirical statement about limitations, like the statement that I can't see ultraviolet light, that it's beyond my capacity. JM: OK; but is the investigation of our cognitive limitations in effect an investigation of the concepts that we have? NC: Well, it may be contradictory, but I don't see any internal contradiction in the idea that we can investigate the nature of our science-forming capacities and discover something about their scope and limits. There's no internal contradiction in that program; whether we can carry it out or not is another question. JM: And common sense has its limitations too . NC: Unless we're angels. Either we're angels or we're organic creatures. If we're organic creatures, every capacity is going to have its scope and limits. That's the nature of the organic world. You ask “Can we ever find the truth in science?” – well, we've run into this question. Peirce, for example, thought that truth is just the limit that science reaches. That's not a good definition of truth. If our cognitive capacities are organic entities, which I take for granted they are, there is some limit they'll reach; but we have no confidence that that's the truth about the world. It may be a part of the truth; but maybe some Martian with different cognitive capacities is laughing at us and asking why we're going off in this false direction all the time. And the Martian might be right.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".