Gender Struggle, Scale, and the Production of Place in the Appalachian Coalfields
Bibliographic record
Abstract
Recent changes in the coal mining industry of Appalachian Kentucky have entailed a widespread economic restructuring with profound effects on the character of the social relations that constitute place. As the traditionally male-dominated mining industry has seen a reduction in employment, there has been a parallel rise in service sector employment, in which women dominate many jobs. Drawing on in-depth interviews with fourteen women living in one coalfield community, we discuss how this economic restructuring has produced a series of struggles between men and women over appropriate gender roles relating to waged work and household work. We also show how these gender struggles—which we suggest are most evident in the microsites of the body and the household—influence the character of networks of social relations at the scale of the locality and, therefore, have an important impact on the production of place and scale. This case study contributes to ongoing discussions of the social production of place and the politics that surround this process. It draws on a feminist theoretical framework to argue that understandings of the production of place cannot disregard the role social relations shaped at the microscale play in shaping place and that our understandings of the politics of place and scale must include the gendered struggles of everyday life.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.023 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".