Roads, Cart Tracks, and Bridle Paths: Land Transportation and the Domestic Economy of Mid-Nineteenth-Century Eastern British North America
Bibliographic record
Abstract
Contemporary observers of mid-nineteenth-century eastern British North America were unanimous in their condemnation of the road network. There is much anecdotal evidence about the poor quality of roads and bridges and the difficulties of overland travel. Seldom is it possible to analyze pre-railroad transportation in less subjective terms. However, a travel census commissioned in 1848 as part of an effort to ascertain the feasibility of potential intercolonial railway routes between Halifax and Quebec provides some rare data on the nature and extent of land transportation in mid-nineteenth-century Nova Scotia, New Brunswick, and Canada East. The focus of this article is on the movement of people and goods documented in the 1848 census. In addition to providing an overview of mid-nineteenth-century transportation and settlement patterns, it contributes to our understanding of the scale and dimensions of internal trade within each of these colonies. While intercolonial travel is shown to have been extremely limited in the pre-railway era, intracolonial travel patterns were complex. Local patterns of land transportation reveal a number of closely circumscribed market hinterlands where trade, exchange, and social interaction linked rural communities to wider colonial and international worlds.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".