Distributive patterns in settler economies: agrarian income inequality during the first globalization (1870-1913)
Bibliographic record
Abstract
The aim of this paper is to identify different distributive patterns in the settler economies (Argentina, Australia, Canada, Chile, New Zealand and Uruguay) during the First Globalization (1870-1913). I present the methodological decisions, discuss my results and propose some conjectures about the long-run evolution of inequality. As agriculture was the most important productive activity in the settler economies and one of the main sectors in leading the land frontier expansion, a study of the generation of income and the evolution of the distribution in this sector is of main interest. First, I estimate the income (or product) per worker in the agriculture and concern for relative performance within the club focusing on (total and sectoral) growth and convergence. After that, I present the notion of functional income distribution and discuss the existence of two distributive patterns. In one of these, the territories that were British colonies and where the capitalist relationships predominated, and in the other, in former colonies of Spain, economic relationships were based on agrarian rental incomes. During the period, income distribution worsened in the Australasian economies and Canada, but it worsened even more in the South American Southern Cone countries. These differences among settler economies are consistent with dissimilar dynamics of expansion onto new land and the conformation of institutional arrangements that promoted unlike patterns of distribution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".