Welfare Levels of the Rural Population in Murcia, 1769-1895. Mortality and Demographic and Economic Instability
Bibliographic record
Abstract
The main objective of this study is to make an estimation of the welfare levels of the Murcian population between the last third of the eighteenth century and the end of the nineteenth century. In order to tackle this topic, we have built several indicators for general mortality, catastrophic mortality, and economic and demographic instability. The main sources that have been used for the development of this research are baptism and burial parish registers, as well as the mercurial of Murcia city. The most relevant conclusions that can be drawn from this essay are: 1st) Murcian welfare levels went through important ups and downs between 1769 and 1889: in the first fifteen years of the 19th century their situation worsened dramatically; there was an improvement between 1815 and 1839 that drove welfare levels above the ones attained during the last quarter of the 18th century; and they deteriorated again from the 1840s till the 1880s, but not as sharply as between 1800 and 1814. 2nd) Almost all the indicators used in this research suggest that the well-being of the regional population had not improved substantially by 1865-1889 when compared with the last quarter of the eighteenth century.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".