On the Rise of the West: Researching Kenneth Pomeranz’s Great Divergence
Bibliographic record
Abstract
For a long time, scholars have tried to explain why Europe alone of the great civilizations of the world achieved a profound transformation in output and productivity in the nineteenth century. Ken Pomeranz’s The Great Divergence is a recent, highly praised intervention in this debate. He argues that, as late as 1800, Chinese living standards and productivity levels were comparable to European ones. What allowed England to industrialize first were plentiful supplies of coal and vast land-saving resources in the New World. But Pomeranz’s claims lack empirical credibility. Over the period 1700–1850, most of Western Europe was on a trajectory away from the Malthusian limitations of the old regime as a result of sustained improvements in both land and labor productivity. The ecological benefits provided to England by American imports were not significant compared to the actual and potential expansion of intra-European trade. China was unable to attain any industrial breakthrough despite enjoying a much greater “ecological windfall” from the acquisition of new territories in central and southwestern Asia after 1500.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".