Market access and occupational upgrading: evidence from the 19th century American transportation network
Bibliographic record
Abstract
This article investigates the extent to which county-level market access affects workers’ occupational upgrading and industrial sorting by exploiting the substantial spatial variation and rapid expansion of the United States’ transportation network coverage from 1870 to 1880. First, I find that individuals who enjoyed greater market access in 1880 were more likely to work in higher-paying occupations. Importantly, this result holds across all sectors of employment, for younger and older workers, and for migrants and non-migrants, suggesting that any market size effects on occupational upgrading were not specific to any one group. I also provide results showing that workers were more likely to switch industries within agriculture, but are less likely to do so from manufacturing or services. Finally, I find some evidence of changes to sectoral reallocation, principally away from agriculture, being associated with higher market access. My findings suggest that the expansion of the transportation network in played an important role in determining the type of work Americans performed in the nineteenth century.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".