Grammatical and register variation and change: A multi-corpora perspective on the English genitive
Bibliographic record
Abstract
s- and of- genitive variation 1. a. …the continued callous indifference of the federal government. [Hansard/u/1956] b. The federal government's environmental plan … [Hansard/u/1956] 2. … all Canadians should stand equal before the trials of life and that all Canadians should benefit equally from life's opportunities. [Macleans/o/2006] 3. a. Professor Arnold Toynbee, disposing blandly of the world's various civilizations like a man judging handicrafts, prize cattle or pickles at a country fair, cites Nova Scotia as a classic example of …[Macleans/h/1956] b. …that literally transcends all of the cultures and all of the religions of the world. [Hansard/y/2006] 4. a. …use it to house Canada's first responsible government … [Macleans/h/1956] b. Miss Hardy is doing a work of national importance and polishing the treasures of Canada. [Macleans/h/1956] 5. a. Canada is asked to enter in to some sort of pact whereby she shall bear a share of the military and naval expenditure of Britain … [Macleans/d/1906] b. … those Jacobite survivals who meet in London and Edinburgh and solemnly resolve that it is England's duty to bring back the Stuarts. [Macleans/d/1906] Some recent studies of s- and of- genitive:
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".