Bibliographic record
Abstract
Usage variables usually involve superficial aspects of linguistic structure, but those that are stable and persistent reach deeper into the language faculty. Two grammatical niceties of standard English that are frequently botched even by people who are nominally standard-bearers are Subject-Verb Agreement with dummy subjects (as in There's twelve months in a year for There are twelve months...) and Accusative Case Concord with Conjoined Pronouns (as in Between John and I, we won three games for Between John and me...). Unlike normal variation, the nonstandard variants are not seen as stylistic choices but as mistakes. These usage variables persist not because of failings of the education system but because of the futility of its expectations. The prescribed grammatical forms invoke scope mechanisms that tax human processing capabilities in specific structural configurations. Grammars prescribe forms that the language faculty cannot reliably produce in the multiple tasks involved in ordinary conversation. The discovery of cognitive limitations that override grammatical processing qualifies the strong version of Chomsky's concept of the Language Faculty as an autonomous 'mental organ', and the concept of grammatical processing as hierarchical rather than linear. The persistence of these unstable constructions as grammatical prescriptions reinforces key concepts in variation theory, especially Kroch's concept of standard grammars as ideologically-motivated social constructs.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.028 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".