FROM DUST BOWL TO GREEN CIRCLES: A CASE STUDY OF
Bibliographic record
Abstract
Social, economic, cultural, environmental, and other forces of change constantly are reshaping our communities, or more precisely, communal relations. An issue of particular concern is the changing significance of locality to the structure of communal relations. Specifically, is the relevance of locality to individuals ’ social interactions changing within our modern society? This empirical investigation examined changes in locality-relevant functions in a rural community: Haskell County, Kansas. In the late 1930s and early 1940s, case studies of six rural communities were conducted by the USDA’s Bureau of Agricultural Economics. The communities were chosen to represent a continuum from high community stability to great instability. Sublette, Kansas, locked in the throes of the “dust bowl, ” was viewed as the least stable of the sites. Earl Bell’s (1942) study of Sublette reported on the social and economic situation of Haskell County, and he confirmed and explained the great instability found in this community. Utilizing Bell’s (1942) work as a benchmark, Mays (1968) revisited Haskell County a quarter of a century later. He described a community that recently had achieved relative stability. Among the changes that had occurred since 1940 were: replacement of the wheat monoculture with crop diversity because of irrigation and government programs, replacement of the “gambling mentality ” of farmers with a business/economic rationality, an increase in class stratification, and men being more active than women in formal leadership roles. Like the previous
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| 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".