Indirect Discourse: Parataxis, the Propositional Function Modification, and “That”
Bibliographic record
Abstract
The purpose of this paper is to assess the general viability of Donald Davidson's paratactic theory of indirect discourse, as well as the specific plausibility of a reincarnated form of the Davidsonian paratactic theory, Gary Kemp's propositional paratactic theory. To this end I will provide an introduction to the Davidsonian paratactic theory and the theory's putative strengths, thereafter noting that an argument from ambiguity seems to effectively undermine Davidson's proposal. Subsequently, I will argue that Kemp's modification of Davidson's theory – that is, Kemp's attempt to respond to the ambiguity objection – adequately handles the classic argument from ambiguity but fails in the face of a new problem of ambiguity that I will introduce. Finally, I will argue that there are more devastating and basic problems for the paratactic theory generally, and that even if Kemp's modifications had succeeded, they would not have given adequate plausibility to the paratactic proposal.
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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 | 0.001 | 0.004 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".