Bibliographic record
Abstract
In the first part of the paper (sections I-III), I describe and discuss a kind of knowledge-gathering activity that I call sensory exploration, and motivate the notion that it eliminates grounds for empirical doubt. Sensory exploration is a distinctive source of knowledge, hitherto unrecognized by philosophers. It relies (of course) on the senses; I’ll argue, further, that it does not rely on background non-sensory beliefs. It involves sensory experience (which has been discussed extensively in the philosophical literature), but, as I shall show, it cannot be reduced to sensory experience—both because it involves something more, and because its epistemic authority does not rest on that of experience alone. In the second part of the paper (sections IV-VII), I discuss the epistemic warrant that sensory exploration provides. The position I espouse in this part of the paper somewhat resembles that of G. E. Moore (1959), who thought that clear deliverances of the senses (e.g., “I am standing up, and not either sitting or lying down”) are immune from all doubt. My position is not, however, quite as forward as Moore’s. Sensory exploration can free us of certain sorts of doubt, I argue, but it cannot neutralize sceptical doubt. I will attempt to define and differentiate sceptical and empirical doubt, and thus to delimit the scope of the certainty that sensory exploration is capable of delivering. Cumulatively, the argument of the paper lends support to a central tenet of traditional empiricism, namely that the senses give us autonomous knowledge of a special domain of properties. Thus, my position opposes those who hold that the knowledge given to us by the senses invariably requires background theoretical (i.e., non-sensory) knowledge.
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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 | 0.032 | 0.132 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.054 |
| Scholarly communication | 0.009 | 0.033 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".