Robert Wuthnow . Remaking the Heartland: Middle America since the 1950s . Princeton: Princeton University Press. 2011. Pp. xiii, 358. $35.00.
Bibliographic record
Abstract
In this study, sociologist Robert Wuthnow counters accepted narratives of the Midwest as a region in decline. Rather, Wuthnow contends, the region is characterized by adaptation, much of it for the better, and survival. In the rural heartland (Arkansas, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, and South Dakota) change, not stasis, was the common condition, and the declension narrative only pertains if images of historic midwestern stability are accepted at face value. Furthermore, recovery from the Great Depression took longer and was more painful in the Middle West than scholars and commentators have assumed, and lasted throughout the 1950s. The ensuing postwar readjustment was successful in terms of “bringing economic restructuring to the region, in redistributing the population to take fuller advantage of changing labor markets, and in strengthening its ties to other parts of the country” (p. 16). By 2000, the heartland states had experienced gross domestic product (GDP) growth rates that equaled or excelled those of other states, attracted new residents at a comparable rate with states in other regions, and become more diverse and more tolerant. Wuthnow concludes that the great American midsection is better off than it was sixty years ago.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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".