Predictability in French gender attribution: A corpus analysis
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
This article presents a corpus analysis designed to determine the extent to which noun endings in French are reliable predictors of grammatical gender. A corpus of 9,961 nouns appearing in Le Robert Junior Illustré was analysed according to noun endings, which were operationalised as orthographic representations of rhymes, which consist of either a vowel sound (i.e., a nucleus) in the case of vocalic endings or a vowel-plus-consonant blend (i.e., a nucleus and a coda) in the case of consonantal endings. The analysis classified noun endings as reliably masculine, reliably feminine, or ambiguous, by considering as reliable predictors of grammatical gender any noun ending that predicts the gender of least 90 per cent of all nouns in the corpus with that ending. Results reveal that 81 per cent of all feminine nouns and 80 per cent of all masculine nouns in the corpus are rule governed, having endings that systematically predict their gender. These findings, at odds with traditional grammars, are discussed in terms of their pedagogical implications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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