Three Cheers for Lord Denman: Reformers, the Irish, and Jury Reforms in Nova Scotia, 1833-1845
Bibliographic record
Abstract
This article explores the important place of the jury in the relationship between law, politics, and state in pre-Confederation Nova Scotia. The legislature responded to fears of jury packing by creating more complex procedures for jury selection. These jury selection systems relied for their implementation on committees composed of magistrates and sheriffs, officials who proved unreliable instruments for carrying out a more bureaucratic state policy. Juries also reflected, and influenced, debates about political parties, libel, and the public sphere. In the 1840s, Irish immigrants to Nova Scotia drew upon their experience of packed juries in Ireland to complain that they were systematically excluded from jury service. Political reformers also asserted that officials packed juries against them with their political opponents, especially in high profile libel cases in which tories attempted to silence the increasingly critical reform press. These libel cases highlighted the role of the jury in protecting freedom of the press and therefore reformers’ ability to challenge the tory leadership of the colony. The fierce complaints over jury selection irregularities led to the passage of reform legislation, though a final solution to the politicization of juries remained elusive with the emergence and acceptance of political parties in Nova Scotia.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".