Bibliographic record
Abstract
Abstract In their recent paper, \Epistemology for Beginners: Two to Five-Year-Old Children's Representation of Falsity," Olivier Mascaro and Olivier Morin study the ontogeny of a naive understanding of truth in humans. Their paper is fascinating for several reasons, but most striking is their claim (given a rather optimistic reading of epistemology) that toddlers as young as two can, at times, recognize false from true assertions. Their Optimistic Epistemology Hypothesis holds that children seem to have an innate capacity to represent a state of affairs truthfully. In the following paper, I investigate the problems this research poses for deationist theories of truth. Richard Rorty and Huw Price hold that the best way to understand truth or \the truth" is to understand the necessary conditions required for assertoric practice. Both philosophers present unique and very different deationary theories when it comes to construing truth. I argue that neither philosopher's approach is successful because they focus on truth and fail to recognize truthfulness as a norm of assertoric practice. I show that truthfulness is the elusive third norm of claim-based discourse and is consistent with Mascaro and Morin's findings.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".