Of Palaces, Hunts, and Pork Roast: Deciphering the Last Chapters of the Capitulary of Quierzy (a. 877)
Bibliographic record
Abstract
Politics depends on personal contacts. This is true in today’s world, and it was certainly true in early medieval states. Even in the Carolingian empire, the largest Western polity of the period, power depended on relations built on personal contacts. In an effort to nurture such necessary relationships, the sovereign moved with his court, within a network of important political “communication centres”; in the ninth century, the foremost among these were his palaces, along with certain cities and religious sanctuaries. And thus, in contemporaneous sources, the Latin term palatium often designates not merely a royal residence but the king’s entourage, through a metonymic displacement that shows the importance of palatial grounds in defining meeting spaces that were both physical and relational: coming to the palace, one could hope to see and hear the sovereign. This is why research on the movements of kings (Itinerarforschung) has been vital to recent historiography. It also justifies the considerable efforts invested in the study of palatial sites (Pfalzforschung), notably through archaeology. And it coheres with the central role of the concept of ‘proximity to the king’ (Königsnähe) in Carolingian political historiography.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".