From Gutsherrschaft to Grundherrschaft: Demographic, Monetary, and Fiscal Factors in the Late-medieval Decline of English Manorial Demesne Agriculture
Bibliographic record
Abstract
This study on the late-medieval decline of English manorial demesne agriculture is based on the Germanic paradigm of Gutsherrschaft and Grundherrschaft, which historians have utilized to explain the transformation of feudal agriculture, east of the Elbe River, from the 15th to the 18th centuries. The former is a manorial regime in which the lord derived his incomes primarily from the commercial exploitation of his demesne lands, using the compulsory labour services of servile tenants. The latter is a manorial regime in which the lord derived his incomes instead primarily from cash rents paid by largely free peasants. In East Elbia, the early-modern shift was from Grundherrschaft to Gutsherrschaft. Late medieval manorial England experienced a reverse shift: from Gutsherrschaft to Grundherrschaft. To explain this transformation, this paper employs a supplementary monetary and fiscal model to prove that the standard Ricardian demographic model is insufficient to explain these changes. My monetary model, based on my prior publications on the deflationary consequences of the first late-medieval bullion famine, from ca. 1375 to ca. 1420, demonstrates that all agrarian prices fell (in nominal terms), while the Ricardian model stipulates that the price fall was limited to grains, and further that the consequent rise in living standards would have led to rising livestock product and other agrarian prices. It also demonstrates that the rise in real wages (agrarian) was partly the result of deflation combined with institutional wage stickiness. My fiscal model demonstrates that the imposition of heavy fixed (specific and not ad valorem) taxes on exports of English wools, by so seriously injuring the chief consumers, the woollen draperies in the Low Countries, quickly led to sharply falling wool sales and (real) wool prices. With such a damaging price-cost scissors, English landlords found that the continued commercial exploitation of their demesnes based on grains and wool was no longer profitable, while leasing those lands to free peasants (abolishing most vestiges of serfdom) was very profitable, since the leasehold tenants had to pay rents whose real value rose during the era of this deflation (ca 1375 - ca. 1420).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".