An unlevel playing field: national income estimates and reciprocal comparison in global economic history
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract If we take recent income per capita estimates at face value, they imply that the average medieval European was at least five times ‘better off’ than the average Congolese today. This raises important questions regarding the meaning and applicability of national income estimates throughout time and space, and their use in the analysis of global economic history over the long term. This article asks whether national income estimates have a historical and geographical specificity that renders the ‘data’ increasingly unsuitable and misleading when assessed outside a specific time and place. Taking the concept of ‘reciprocal comparison’ as a starting point, it further questions whether national income estimates make sense in pre-and post-industrial societies, in decentralized societies, and in polities outside the temperate zone. One of the major challenges in global history is Eurocentrism. Resisting the temptation to compare the world according to the most conventional development measure might be a recommended step in overcoming this bias.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it