Summary justice in the city : a selection of cases heard at the Guildhall Justice Room, 1752-1781
Bibliographic record
Abstract
For centuries, the City of London's Lord Mayor and Aldermen have headed various courts and tribunals as part of their official obligations. In the City's Guildhall, Londoners from all walks of life could appear before an alderman sitting as a magistrate in the room and initiate a criminal complaint when they were the victims of crime. But what actually happened in those initial hearings between the accuser, the accused and the magistrate has remained largely obscured to history. These records shed light on the earliest phases of a criminal prosecution and reveal the routines of criminal justice administration in the eighteenth-century metropolis. From the fragmentary minutes of the proceedings conducted before London's aldermen, who sat for a part of every working day as Justices of the Peace, we learn of the petty squabbles of the City's poor with parish officials, the ready resort to physical violence in public and private spheres, the steady campaign against prostitution, and the growing professionalism of the parish constables who policed London before the arrival of the Metropolitan Police.The records will be of interest to historians of London, social historians of crime, genealogists and scholars interested in summary or pre-trial procedures in early modern England; they are presented here with introduction and explanatory notes. Greg T. Smith is Associate Professor of History at the University of Manitoba.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".