Bibliographic record
Abstract
Rice (2006) presents a unified analysis of Norwegian word stress that applies equally to native words and to loanwords. In this analysis, stress is oriented to the right edge of the word, which suggests that the loanwords were responsible for changing what was originally a left-oriented grammar of stress. In this paper I consider a similar reorientation that took place in the history of English, also under the influence of Romance loanwords. Closer examination shows that the two cases appear to be different. Many loanwords of the sort that caused a change in Norwegian entered Middle English without causing any significant change in English stress. It was only in the Early Modern English period that the loanwords were able to impose a right-oriented stress pattern on English. Rice (2006) observes that the loanwords were able to change the Norwegian stress pattern without overtly contradicting the native words; that is, the loanwords could make a change only in aspects of the grammar where the native words were ambiguous. I argue that this principle also accounts for the English case.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".