Bibliographic record
Abstract
Donald Davidson's approach to meaning can be understood as a synthesis of the divergent positions of Grice and Derrida. I argue, following Davidson, that intentions should be afforded a central role in determining meanings, but that this centrality does not mean that intentions absolutely fix the meaning of a language act. Davidson borrows heavily from Grice, who, I contend, is committed to some version of logoi or self-interpreting units of meaning unmediated by a system of signifiers. Derrida, taking the contrasting view, argues against any notion oflogoi. Derrida argues further that truth, as philosophers have typically thought of it, depends on the existence of self-interpreting signs. Derrida' s rejection of logocentrism seems to entail a rejection of truth as traditionally conceived by philosophers. Davidson, on the other hand, makes truth central in his account of meaning by providing an account of truth that does not depend on the existence of logoi. My central claim is that Davidson, although relying on a Gricean view of speaker intentions and affording truth a central role, does not violate any of Derrida' s primary theses about truth and the nature of meaning.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".