Bibliographic record
Abstract
This volume has been many years in the making. I first discovered examples of wives and husbands suing each other in Requests in 1989 while pursuing doctoral research. Pat Stretton and Jane Martindale independently suggested that the cases were worthy of publication, and Jane helped to bring this idea to the attention of the literary editors of the Royal Historical Society. I thank them both. Since then the editors of the Camden Series, Andrew Pettegree and Ian Archer, have provided support and shown unstinting patience for a project that has seasonally burst the banks of its projected deadlines. I am grateful to them, to the anonymous reviewer of the original proposal for pointing out the need to determine the frequency with which cases of this type came into Requests, and to the National Archives for permitting the cases to be reproduced. For financial support I wish to acknowledge the generosity of the Social Sciences and Humanities Research Council of Canada, grant-giving bodies within Waikato University, Dalhousie University, and Saint Mary's University, and Lyndan Warner. A number of scholars, archivists, and friends have provided advice as well as technical help in identifying legal counsel, deciphering handwriting, and translating Latin abbreviations. I would like to thank Christopher Brooks, Sara Butler, Sabina Flannagan, Elizabeth Foyster, Lamar Hill, Martin Holt, Wilfrid Prest, and the helpful staff at the National Archives, especially Amanda Bevan, Sean Cunningham, Alistair Hanson, and Malcolm Mercer. All of them are absolved of responsibility for any of the errors that remain. For the generosity of their hospitality during the compiling and editing of this volume, I would like to offer my gratitude to Gareth Edwards, Frances Wedgwood, Nick Manglaras, Francesca Amirato, and the Tewsons. Final thanks go to Lyndan Warner, for her support, her comments on the introduction, and her willingness to look after our children while I made annual visits to London and Kew.
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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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.484 | 0.340 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".