On the reconstruction of experiential constructions in (Late) Proto-Indo-European
Bibliographic record
Abstract
In this paper I will attempt to reconstruct the (Late) PIE syntax of experiential constructions for three classes of verbs: in (1) and (2) for verbs of cognition and perception, in (3) verbs denoting changes in bodily states, and in (4) verbs of deontic and epistemic modality. In (5) I will make some proposals regarding typology and syntax of experiential constructions in terms of several diachronic layers. I will also try to ascertain whether we can reconstruct the so-called ‘oblique subject’ typology for the (Late) PIE and, if not, at which intermediate period in its trajectory to the current state of affairs we can discern the appearance of oblique (or rather ‘secondary’) subjects. On the whole, I will be more preoccupied with morphological, semantic and pragmatic properties of the experiential constructions in Ancient IE (Greek, Latin, Sanskrit, Gothic, Old Slavic) and Modern Germanic, Baltic and Slavic languages than with the issue of ‘subjecthood’ in terms of formal syntax. In conclusion, I will submit that the cognitive approach presents a number of important correctives to more formal syntactic approach into the typology and diachrony of experiential constructions across the spectrum of Indo-European languages.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".