Reconstructing the Transport Network of Ancient China and its Relationship to Social Networks
Bibliographic record
Abstract
This study reconstructs ancient China's transport system, exploring its intersection with societal networks. We begin by procuring population data indicative of years 2, 742, 1102, and 1522. The transportation matrix, inclusive of roads, rivers, and canals, is subsequently reconstituted. In continuation, we ascertain the transport accessibility for heavy goods. Our accessibility model reveals that history lends itself to a more coherent explanation through quantitative research. We then deploy a gravity model to examine the correlation between transport systems and social networks. The model delineates how transport, particularly travel duration, influenced societal interconnections. The implemented gravity model further highlights the steady deterrent of travel time, suggesting that transport infrastructure might sustainably govern social networks on a historic spectrum. Finally, our research draws on the analysis of five key capitals throughout history, along with other connections inadequately modeled by the gravity approach, to discuss the self-perpetuation effects of social networks. We discern that cities with elevated political stature or a sizable population/economic foundation tend to exhibit a more robust self-reinforcing influence on their social networks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".