Castle Construction, Conquest and Compensation ( <i>The Christine Mahany Memorial Lecture</i> )
Bibliographic record
Abstract
For older members of the Battle Conference the most abiding memory of Christine Mahany (15 January 1939–13 July 2016) (Fig. 1) will almost certainly be of her sitting at the bar in The Chequers, pint in hand, deep in conversation with Allen Brown, while George, her beloved labrador, patiently languished at her feet. Dogs were a frequent subject of passionate discussion. It was, after all, a time when canine delegates Matilda and Offa were cast in the crucial role of celebrity judges who voiced their opinion of tendentious arguments and windy papers with a yawn or a howl. As often as not, though, the chat was about archaeology or history, or, more precisely, archaeology and history. As odd as it may seem today, the relationship between the two subjects was something of an issue in the 1970s and 1980s. Archaeology as the handmaiden to history was still a cheap put-down that was bandied about in historical circles. Chris came to Battle as an advocate of equality and common interest. After something of a false start, her background was copper-bottomed archaeology. She studied zoology as a student but spent much of her time in Leicester's New Walk Museum sorting pottery sherds and the like, and so after graduation she was drawn to archaeology as a career. She cut her teeth under the tutelage of Philip Rahtz, the great exponent of open-area excavation, digging on seminal early medieval sites such as Cheddar and Cannington. Thereafter she became an itinerant archaeologist for the Ministry of Public Buildings and Works in her own right, supervising a wide range of sites. Her excavation of the small Roman town of Alcester in Warwickshire was a particular achievement. Temperamentally, however, her interests had always gravitated towards medieval archaeology, and her appointment as director of the Stamford Archaeological Research Committee in 1966 gave her the opportunity to indulge them. She was to stay in Stamford for the rest of her career. Her appointment came at an opportune time. After a decade of inappropriate post-war development – vandalism is probably a more appropriate term – the historic core of Stamford was designated as the first conservation area in Britain. Chris's brief was to recover its archaeology and produce a coherent account of its origins and growth. Twenty or so excavations and numerous watching briefs followed, covering the full range of medieval life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.131 | 0.032 |
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".