The Inequality of Pay in Pre-modern Germany, Late 15<sup>th</sup> Century to 1889
Bibliographic record
Abstract
Abstract The study explores relative labour scarcity in a broad range of activities and relates it to the long-run dynamics of structural change, supply and demand of human capital, and the inequality between men and women. It builds on two recent compilations of wage data and complements these with additional information, particularly on wages in agriculture. From the second quarter of the seventeenth century the skill premium was stable; the first phase of industrialization did not lead to a differentiation of the individual return to human capital. Labour demand from the modern sector stabilized real wages of males from the second quarter of the eighteenth century at least and increased them from the mid-1850s onwards. This opened a wedge between the agricultural and the non-agricultural sectors already for considerable time before the beginnings of industrialization. Finally, the modern era saw two phases of labour market segmentation along gender lines, one in the later sixteenth and the early seventeenth centuries, the other from the 1840s to the 1870s.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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; both teacher heads agree on what is shown here.
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".