The Tennessee-Virginia Tri-Cities: Urbanization in Appalachia, 1900–1950
Bibliographic record
Abstract
In 1900, the Appalachian region of northeast Tennessee and southwest Virginia began to change. The inhabitants were dependent on the resources of the rural land, but the arrival of railroads spawned industrialization. Over the next several decades, families moved down from the mountains into the valley of East Tennessee as workers took jobs in the developing urban centers. Country stores, two-lane roads, and cornfields would eventually give way to cities, multi-lane highways, and new housing. The Tri-Cities—Kingsport, Johnson City, and Bristol—were starting to form. In this carefully documented book, Tom Lee uses archival material, newspapers, memoirs, and current scholarship in Appalachian studies to examine the economic changes that took place in the Tri-Cities region from 1900 to 1950. With modernization and urbanization, an urban-industrial strategy of economic development evolved. The entry of extractive industry into the mountains established the power of the urban elite to shape rural life. Local businessmen saw the route to financial strength in the recruitment of low-wage industry. Workers left struggling farms for factory jobs. This urban-rural relationship supported the Tri-Cities’ manufacturing economy and gave power to the area’s elite. The New Deal and the Second World War broadened this relationship as federal funding sustained the economy. The advantages of urban centers after decades of development left rural communities on the verge of disappearance and dependent on the jobs, opportunities, and economic vision of the cities. By 1950, the power of Appalachia’s elite over the people of the region had extended beyond urban boundaries and brought about the conditions necessary for the creation of the metropolitan Tri-Cities area of today. Readers will gain a better understanding of the complexity of modernization in Appalachia and the rural South from this engaging book.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".