Bibliographic record
Abstract
Newfoundland English as a relic variety In the unravelling of the complex history of transported Englishes, a special role is played by the island of Newfoundland – which in 1949, after almost four hundred years of existence as a British colony, became along with Labrador the tenth province of Canada. From a sociohistorical perspective, the speech of the island occupies a unique position in the investigation of transplanted English, for several important reasons. First of all, Newfoundland varieties are among the oldest of any transported English: the island was claimed for the British crown in 1583, and English settlement dates from the first decade of the seventeenth century. Secondly, the origins of British and Irish emigrants to Newfoundland have been documented to a degree virtually unprecedented in the history of New World settlement, a task facilitated by the fact that the two major source areas for emigration were highly geographically restricted. As the historical geographer John Mannion (1977:7) has observed, ‘It is unlikely that any other province or state in contemporary North America drew such an overwhelming proportion of its immigrants from such localized source areas in the European homeland over so substantial a period of time.’ Thirdly, as an island off the east coast of North America, Newfoundland remained relatively isolated from the rest of the continent until the mid twentieth century, the majority of residents having little contact with mainland speech varieties.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".