Connectivity, Migrations, Mobility, and Networks
Bibliographic record
Abstract
Abstract Chapter 7 explores how transport networks and infrastructure, and their change over time, are fundamental to understand population movements, and the supply of cities and their costs. Besides, transport infrastructures are proxies for population settlement. The first part of the chapter studies whether communications in Hispania were adequate for the economic and demographic needs of its population and how they changed over time from the pre-Roman to Roman period. To do so, GIS is employed to carry out a network analysis of the maritime and road networks of the different periods. The use of macro- and micro-scale analyses provides a clearer picture of the development of the urbanization rate and demographic movements. The second part of the chapter looks at who migrated towards the province and why over time , l ooking not only at permanent mobility, but also at the many temporary and seasonal movements that occurred within the province. Certain tasks, such as those related to agriculture, trade, construction, and harbours, were only possible during the spring and summer seasons. Similarly, some professions, such as military service and domestic work, occupied young people who would move to urban or military sites for a limited period and then return to their hometowns as adults.
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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) | 0.000 | 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) | 0.013 | 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".