Surplus, Scarcity and Soil Fertility in Pre-Industrial Austrian Agriculture—The Sustainability Costs of Inequality
Bibliographic record
Abstract
This paper takes a Long-Term Socio-Ecological Research (LTSER) perspective to integrate important aspects of social inequality into Socio-Ecological Metabolism (SEM) research. SEM has dealt with biophysical features of pre-industrial agricultural systems from a largely apolitical perspective, neglecting social relations and conditions of peasant production and reproduction. One of the politically and economically most important manorial systems in Early Modern Austria (Grundherrschaft Grafenegg) serves as a case study to reconstruct the unequal distribution of central resources between ruling landlords and subjected peasants. We show that peasant land use systems generated small surpluses only, whereas landlords enjoyed significant economies of scale. Furthermore, we explore what these conditions of landlord surplus and peasant scarcity implied for their respective agro-ecological sustainability. Finally, we argue that within pre-industrial agrarian systems sustainability costs of inequality were severely limiting margins for agricultural intensification and growth of peasant economies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".