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Record W1975088579 · doi:10.1068/a35230

Gender Struggle, Scale, and the Production of Place in the Appalachian Coalfields

2004· article· en· W1975088579 on OpenAlexaff
Christiana Miewald, Eugene McCann

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRestructuringPoliticsSociologyScale (ratio)Production (economics)Tertiary sector of the economyRelations of productionSocial relationMode of productionGender studiesEconomic restructuringPolitical economyPolitical scienceEconomic growthSocial scienceEconomyEconomicsLawGeography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.224
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2004
Admission routes1
Has abstractyes

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