Vindicating the Future A Dialogical Stance on Belnap's Approach to Tomorrow's Sea Battle
Bibliographic record
Abstract
In several texts, some authored by himself alone and some in collaboration N. D. Belnap proposed a pragmatist approach to predictions and further speech acts such as promising, betting, and wondering, in an indeterministic setting within a branching structure that shapes the future course of events. In the joint paper "Future Contingents and the Battle Tomorrow", M. Perloff and N. E. Belnap discuss Aristotle's famous example in the context of STIT-logic. In particular, the paper studies the pragmatics of predictions of future contingents under the background of the 480 BCE battle of Salamis: the general commanding the Greek Athenian fleet predicts that a battle will be fought on the sea while the Spartan general denies it. According to Perloff and Belnap's analysis, this kind of prediction is neither true nor necessary at the moment of utterance, but can be vindicated or impugned, retrospectively. The central thought of the present paper is that vindication is a dialogical process associated to statements made. In the particular case that the statement expresses a prediction, the dialogical process involves plays on the settled past truth of the predicted contingent future. This way of analysing Tomorrow's Sea Battle highlights the interplay of the ontological perspective and the linguistic perspective, where vindication or impugnment of the predictions are under scrutiny.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".