Meditation Three (I) : The Meditator discovers how to distinguish true from false propositions by reference to the clarity and distinctness of his ideas and considers whether God is merely a subjective idea
Bibliographic record
Abstract
CLEAR AND DISTINCT PERCEPTION – TRUTH (AT VII:34–6) I will now shut my eyes, stop my ears, and withdraw all my senses. I will eliminate from my thoughts all images of bodily things, or rather, since this is hardly possible, I will regard all such images as vacuous, false and worthless. I will converse with myself and scrutinize myself a little more deeply; and in this way I will attempt to achieve, little by little, a more intimate knowledge of myself. ( vii :34) The Meditator continues with his experiment in Hyperbolic Doubt, maintaining the fiction of the malevolent Demon. When we left him at the end of Meditation Two , his belief-set was as it is represented in Figure 16. The Meditator reasons that he can add a new, significant item to his belief-set. He now “knows what is required for being certain of anything.” He is in a position, he finds, to lay down a general rule that will serve as the sought-for filter that can separate true from false . The filter is the test or criterion of the clarity and distinctness of his perceptions. Justifying, or certifying, this filter as “performing as advertised” takes up, as one might expect, the entirety of Meditation Three . I am certain that I am a thinking thing … In this first item of knowledge there is simply a clear and distinct perception of what I am asserting; this would not be enough to make me certain of the truth of the matter if it could ever turn out that something which I perceived with such clarity and distinctness was false.[…]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".