Bibliographic record
Abstract
This chapter summarises the preceding discussions and presents some concluding thoughts from the authors. Earls Colne was situated within one of the most commercially developed areas of late medieval England. It was on the fringes of London, which in turn implies a regionally specific historical experience. The arrival of a resident landlord in a village was a common experience in the century after 1540. Where this occurred, personal supervision replaced power structures that had relied on monastic, aristocratic or crown stewards. In Earls Colne, this change disturbed a situation in which the village had sometimes taken liberties over its rights or lapsed into self-government. The Harlakendens remained a presence in the village for most of the following century, but the landlord interest in Earls Colne did not develop beyond the limits established then. Earls Colne never had a great nineteenth-century house or park, or model arable farms staffed by day labourers, nor was it incorporated into a great estate. It remained a parish of variegated holdings, with landowners both large and small, because it failed to follow the developmental paths taken by some of the other English villages that have been the subject of exhaustive historical study.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.267 | 0.080 |
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".