Bibliographic record
Abstract
This paper is in four parts. The first sets out the debate between those who wished England to have only a professional army, and those who sought to supplement it with a citizen militia. This debate is crucial for understanding The History of the Proceedings in the Case of Margaret, Commonly Called Peg, Only Lawful Sister to John Bull, Esq. This political satire (commonly known as Sister Peg) is about the successful struggle to re-establish the militia in England in 1757, and the unsuccessful attempt to extend the measure to Scotland. Adam Ferguson was in favour of Scotland having a militia, whereas some have claimed that Hume was against it. It is argued that Hume supported the measure. In the second part Sister Peg is briefly compared to Dr John Arbuthnot’s The History of John Bull, of which it is an imitation and sequel. In the third part the issue of the disputed authorship of Sister Peg is considered at length and Hume’s claim to have written it is compared to the Rev. Alexander Carlyle’s account that Ferguson alone wrote the work. Which of the two accounts is reliable? Richard B. Sher, in an article in this journal, assumes that Carlyle’s account is reliable, and takes issue with my arguments for reattributing the satire to Hume. It is argued that none of his arguments is successful, and that simply assuming the reliability of Carlyle’s account begs the question. In the fourth part some emendations made by Ferguson in his copy of Sister Peg are set out so that readers may see for themselves that they are almost certainly non-authorial.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".