El crédito rural: Los censos. Estudio del préstamo censal en la comarca de la Sagra en el Setecientos
Bibliographic record
Abstract
Los censos constituyen un instrumento crediticio cuya valoración ha sido objeto de \nnumerosas controversias, tanto por los economistas de la época como por los historiadores \nactuales. \nCon este trabajo intentamos acercarnos a su conocimiento, analizando aspectos \ncomo la distribución geográfica de los censatarios, la sociología tanto de los acreedores \ncomo de los deudores, las cuantías que se prestan, la hipoteca con que se cargaban o la \nredención de los censos. Se pretende ver qué incidencia tuvo en la comarca de la Sagra, \ndurante el siglo XVIII, para poder sacar unas conclusiones que nos permitan emitir un \njuicio sobre sus ventajas o inconvenientes como instrumento de préstamo. \nComo fuente principal se han utilizado de forma exhaustiva las escrituras de imposición \ny de redención de censos existentes en los protocolos notariales del Archivo Histórico \nProvincial de Toledo
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".