Migration networks in the configuration of mining communities in Spain in the nineteenth century: Linares
Bibliographic record
Abstract
Abstract This research examines migration in Linares during the third quarter of the nineteenth century, focusing on migration chains. The city experienced a significant increase in population due to the mining boom, which led to an almost sixfold increase in the population over a period of 30 years. Using data from the 1873 population register, which includes more than 22,500 individuals, this study confirms the effectiveness of the migration chain framework in analyzing internal migration during the preindustrial and early industrialization periods. This approach has revealed the significant influence of this form of social capital in determining migratory flows to Linares, highlighting the importance of places of origin in the spatial distribution of the city and in the occupational specialization of the migrant population. The findings suggest that migratory chains played a key role in providing information about opportunities at the destination, as well as in reducing the costs associated with the search for employment and housing.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".