Bibliographic record
Abstract
Abstract This chapter presents the current lack of consensus regarding Berkeley’s arguments for idealism. Discussed first are ways of interpreting Berkeley’s conclusions, as partial idealism, limited idealism, or total idealism. Interpretations of Berkeley’s justifications for idealism are then organized into three categories: the intuitively known; the demonstratively known, metaphysical; and the demonstratively known, epistemological. Berkeley’s reasons from Principles 1–6 (the semantic argument and the two simple arguments) are presented, followed by the reason commonly adduced from Berkeley’s immaterialism (the likeness principle argument). Discussion of the master argument then follows. Next, attention is directed at Berkeley’s reasons from the Three Dialogues, where the pain-pleasure argument and the argument from perceptual relativity are presented as attempts to justify key presumptions behind the simple arguments of the Principles. The master argument briefly reappears as well. The chapter concludes with discussion of the attempts to understand the conceptual basis of the arguments for idealism: heterogeneity, anti-abstractionism, and immediate perception.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".