Pathways of Counterfactual Markings: A Diachronic Typology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous accounts show that markings of CF (counterfactual) clauses tend to be complex. One frequent combination of markers that shows up in many languages is that of a past tense together with perfect in past CFs. According to Dahl (1997), the stacking use of CF markings consists of elements of varying historical layers. This motivates a closer look at the diachronic history of each marking in the combinations that do occur. This paper is therefore devoted to a diachronic development of CF markings. A diachronic study of frequently used CF markers such as past tense, perfective/imperfective aspect, irrealis mood markers is conducted. I propose a cross-linguistic whole life-cycle of CF markers which start as pragmatic clues, termed as CFEnhancing (Counterfactual Enhancing) markers in this paper. The following part will address the question concerning the origins of counterfactuality ahead of the main discussion.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it