Bibliographic record
Abstract
The death of William FitzOsbert is one of the most famous and dramatic incidents in the history of medieval London. In 1196 long simmering tensions concerning the manner in which the burden of taxation was being divided finally boiled over. The advocate for the poor and middling members of the community, William FitzOsbert (also known as William cum barba, or Longbeard), took refuge in St Mary le Bow church but, following a brief siege that culminated in the burning of the steeple, he was captured and brutally executed. Accounts of the incident, written by contemporary chroniclers, provide a glimpse into the urban political community. The chroniclers have important things to say about the sources of conflict within civic society, but this paper focuses on assessing the significance of this incident for our understanding of civic governance in medieval London. The accounts of the rise and fall of William FitzOsbert are intriguing, because they show dissension within the civic community, and describe how a significant faction of discontented citizens attempted to express their views and agitate for change. The chronicle accounts provide evidence that allows historians to consider the role of popular pressure in civic politics, at a time when the city was acquiring a new political identity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".