Bibliographic record
Abstract
Steamships removed the message speed limit imposed by horses and sails, and telegraphy made communication almost instantaneous. Top state sizes expanded accordingly. Graphs superimpose the growth–decline curves of major post−1800 Engineer Empires. Britain became the largest empire ever (24% of world dry land area), but it lasted at more than half of its maximum size only for 110 years, comparable to nomad Xiongnu. State collapse in China also made Britain briefly the most populous of the world, due to its control of India. For most of the Engineer period Russia has been the largest and China (Qing and People’s Republic) the most populous. India’s population surpassed China’s in 2023. At the 1925 peak of European domination, 64% of Earth’s dry land area was ruled from Europe. It is now down to 21%, mainly Siberia. But European-stock Russia, USA, Canada, Brazil, and Australia remain part of the top seven, along with China and India. Population proportions differ. Since 1800, six to ten states have held more than 2% of Earth’s dry land area. Every half-century, three to four have entered or exited this category. By this pattern, 2000−2050 has been unusually quiet, up to now.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.032 |
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".