Bibliographic record
Abstract
What is the cognitive value of the concept of truth? What epistemic difference does the concept of truth make to those who grasp it? This paper employs a new perspective for thinking about the concept of truth and recent debates concerning it, organized around the question of thecognitive valueof the concept of truth. The paper aims to defend a substantively correct and dialectically optimal account of the cognitive value of the concept of truth. This perspective is employed in understanding the critical discussion around what Hartry Field (2001a) has called “the incorporation model” for extending a deflationary view of truth to foreign sentences. Field's original intentions in discussing the incorporation model were to defend the deflationary view from some counterintuitive consequences concerning the understanding of truth attributions to foreign sentences. However, more recently, philosophers unencumbered by deflationary commitments have taken over the incorporation model for their own inflationary purposes. In particular, and in my terms, these philosophers can be understood as making what I argue is the ultimately too radical suggestion that the cognitive value of the concept of truth is to allow the incorporation not only of the linguistically foreign, but also of theconceptually alien. I clarify this dialectic en route to explaining and arguing forthe cognitive inflationary view, according to which the cognitive value of the concept of truth is is to make possible the proprietary kind and quality of knowledge allowed by reflective clarity over the concepts and thoughts that one already has.
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 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".