Bibliographic record
Abstract
In 1848, Annette Meyers, a domestic servant, murdered Henry Ducker, a private in the Coldstream Guards, as he walked through St. James’s Park. Meyers freely admitted to having shot him and claimed she had long planned to do so. In spite of these admissions, the media constructed a version of the events in which she was the greater victim, and the murdered man was the villain. This article examines how two broadsides, a chapbook and extensive newspaper reports promoted sympathy for Meyers, and why the public believed it appropriate to see her as an object of sympathy. It also demonstrates the complicated nature of ideological transitions: they are not straight forward linear progressions but can be complicated and contradictory. New notions of gender — bourgeois masculinity and the cult of domesticity — and shifts in legal thought, especially with respect to the legal defence of provocation, caused tensions between the media and the courts. Defending older understandings of provocation, the newspapers made rare criticisms of the trial judge, the sentence, and the justice system itself, critiques which were widely shared by middle-class readers, and which might have proven dangerous during a turbulent decade like the 1840s. The various forms of media acted together, although not in an orchestrated fashion, to force the Home Secretary to overrule the judge, and to reduce Meyers’ sentence to two years imprisonment to be followed by transportation for life to Australia.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.011 | 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".