Re-Thinking Gareth Evans’ Approach to Indexical Sense and the Problem of Tracking Thoughts
Bibliographic record
Abstract
In “Understanding Demonstratives”, Gareth Evans bites the bullet regarding Rip van Winkle cases in cognitive dynamics: the fact that Rip sleeps for twenty years and completely loses track of time means he is unable to retain his original belief that “Today is a fine day”. In this paper, the author argues that Evans need not bite this bullet because there are resources in his account of the cognitive dynamics involved in belief retention developed inThe Varieties of Referenceto successfully confront the challenge posed by the Rip van Winkle case. In particular, when we combine the two central elements of Evans’s cognitive dynamics – the skill of keeping track of one’s spatio-temporal location in addition to memory – it is possible to arrive at the conclusion that it is indeed possible for Rip to retain and re-express his original belief.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.038 |
| Scholarly communication | 0.007 | 0.024 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".