The trajectory of φ-features on Old French D and n
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Old French (OF) determiners (D), which are optional, show a three-way split between definite ( def ), indefinite( indf ), and expletive( expl) D. We develop a nano-syntactic analysis of these three paradigms, according to which the nominal spine is associated with a series of functional heads that include Number, Gender, D, and Kase. We test the predictions of the formal analysis with a quantitative analysis of corpus data from two 12 th century Anglo-Norman texts – Le voyage de saint Brendan ( B ) and Lais de Marie de France ( MdF ) – which indicates that over a 60-year span, there are changes in the distribution of D. This presents itself in three ways. First, a decline in expletive D in MdF correlates with an increase in the use of D with masculine ( m ) non-count nouns ( n NON-CT ) Second, while B lacks an overt indefinite plural ( pl ) D, MdF has one in the form of des . Third, with count nouns( n CT ), while feminine ( f ) nouns favour the absence of determiners in B , there is no gender effect in MdF . While the first two changes are predicted by the formal analysis, the third is not. More broadly, the results of our quantitative study provide a more nuanced picture of the factors that govern the distribution of D in OF: they confirm that – relative to conditioning the absence of D (D-drop) – definiteness, grammatical function, and number are stable factors, gender is not a stable factor, and word order does not play a significant role.
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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 | 0.002 | 0.040 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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