How Can Semantics Avoid the Troubles with the Analytic/Synthetic Distinction?
Bibliographic record
Abstract
Abstract At least since Quine (From a logical point of view. Harvard University Press, Cambridge, MA, 1953) it has been suspected that a semantic theory that rests on defining features, or on what are taken to be “analytic” properties bearing on the content of lexical items, rests on a fault line. Simply put, there is no criterion for determining which features or propertiesFeatures are to be analytic and which ones are to be synthetic or contingent on experience. Deep down, our concern is what cognitive science and its several competing semantic theories have to offer in terms of solution. We analyze a few cases, which run into trouble by appealing to analyticity, and propose our own solution to this problem: a version of atomism cum inferences, which we think it is the only way out of the dead-end of analyticity. We start off by discussing several guiding assumptions regarding cognitive architecture and on what we take to be methodological imperatives for doing semantics within cognitive science—that is a semantics that is concerned with accounting for mental states. We then discuss theoretical perspectives on lexical causatives and the so-called “coercion” phenomenon or, in our preferred terminology, indeterminacy. And we advance, even if briefly, a proposal for the representation and processing of conceptual content that does away with the analytic/synthetic distinction. We argue that the only account of mental content that does away with the analytic/synthetic distinction is atomism. The version of atomism that we sketch accounts for the purported effects of analyticity with a system of inferences that are in essence synthetic and, thus, not content constitutive.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.038 |
| Scholarly communication | 0.010 | 0.047 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".