The Effects of Land Inequality on Economic Growth: A Regional and Comparative Study, 1950-1970
Bibliographic record
Abstract
This paper seeks to improve regional and national databases. Apart from Taylor and \nHudson (1972), Deininger and Squire (1999), and Frankema (2008), there are no estimates \nfor land inequality, that is, landgini indices for Latin America for the period 1950-1970. \nFurthermore, the estimates of these authors are incomplete and only focus on the national \nlevel. The objective of this paper is to fill in the gaps in the literature by offering new and \noriginal estimates of landgini indices for all Latin American countries, and by extension for \nthe United States, Canada, and Western Europe, both nationally and regionally. The paper \npresents the methodology and sources used to estimate the landginis indices, compare \nthem with previous estimates and offer a more complete and global picture of land \ninequality. This paper presents the largest compilation of data on land inequality for this \nperiod. Furthermore, thanks to the new and original database offered in this paper, more \ncomplete regional and national studies can be derived.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".