R. Bitterman & M.E. McCallum, Lady Landlords of Prince Edward\n-Island: Imperial Dreams and the Defence of Property
Bibliographic record
Abstract
On 23 July 23 1767, some four years after its acquisition of Saint John's Island [now Prince Edward Island] in the 1763 Treaty of Paris, Britain held a one-day lottery through which it distributed almost the entire island in sixty-six lots [townships] of about 20,000 acres each.' Many lots went to individuals, civil and military servants of the crown, including such notables as John Pownall, secretary to the Lords of Trade, and Admiral Augustus Keppel. Although none of the proprietors met the principal condition oftheir grant-that they settle the land within ten years with one Protestant settler for every 200 acres-the proprietorial system remained in place for over a century. Some large proprietors lost their lands when they were sold by the local government for failure to pay quit rents, while others sold because they were worried about such legal action, with the result that by the 1830s about one-fifth of Island land was in the hands of small farmer-owners. Yet the vast majority of the land continued to be owned by descendants of the original large proprietors, and mostly worked by tenant farmers. Most of the large proprietors were absentee landlords, residents of the United Kingdom.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.052 | 0.011 |
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".