On Common Solutions to the Liar and the Sorites
Bibliographic record
Abstract
In this dissertation I examine some of the most relevant proposals of common solutions to the Liar and the Sorites paradoxes. In order to do that, I present first a definition of what a paradox is so that, with this at hand, I can characterize in detail what should we expect from a common solution to a given collection of paradoxes. Next, I look into the reasons we might have to endorse a common solution to a group of paradoxes and some consequences are drawn with respect to Vann McGee's and Graham Priest's proposals to cope with both the Liar and the Sorites paradoxes, In the next chapters, three authors are examined in some detail. First, Jamie Tappenden's account is judged inappropriate, specially in the case of the Liar paradox. With respect to the Sorites, it is showed to be at least as problematic as Supervaluational approaches. Second, Paul Horwich's epistemicist proposal is examined with a special focus on the treatment of the Liar paradox. Horwich's account about how to construct his theory of truth is formalized and critically discussed with the use of a fixed-point construction. In the last chapter, I introduce and discuss some logics based on the work of Hartry Field that use two conditionals in a language with a truth predicate and vague predicates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".