Landownership Distribution, Socio‐Economic Precariousness and Empowerment: The Role of Small Peasants in <scp>M</scp>aresme County (<scp>C</scp>atalonia, <scp>S</scp>pain) from 1850 to the 1950s
Bibliographic record
Abstract
I present fresh data that show the leading role played by smallholder peasants in land‐use intensification, technical improvement and landscape transformation in Maresme County (province of Barcelona, Spain) between 1850 and the 1950s. As a reaction to their precarious situation, caused by an unequal landownership distribution (which is assessed by looking at the minimum‐income and maximum workable farm sizes), smallholders drove agrarian changes in this coastal Mediterranean area. The results of their individual efforts, and their collective action through social mobilization and cooperatives, entailed a socio‐economic and political improvement, especially in denser populated areas closer to markets, until the arrival of Franco's regime.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".