Queering the Countryside: New Frontiers in Rural Queer Studies
Bibliographic record
Abstract
Choice Outstanding Academic Title of 2016Rural queer experience is often hidden or ignored, and presumed to be alienating, lacking, and incomplete without connections to a gay culture that exists in an urban elsewhere. Queering the Countryside offers the first comprehensive look at queer desires found in rural America from a genuinely multi-disciplinary perspective. This collection of original essays confronts the assumption that queer desires depend upon urban life for meaning.By considering rural queer life, the contributors challenge readers to explore queer experiences in ways that give greater context and texture to modern practices of identity formation. The book’s focus on understudied rural spaces throws into relief the overemphasis of urban locations and structures in the current political and theoretical work on queer sexualities and genders. Queering the Countryside highlights the need to rethink notions of "the closet" and "coming out" and the characterizations of non-urban sexualities and genders as "isolated" and in need of "outreach." Contributors focus on a range of topics—some obvious, some delightfully unexpected—from the legacy of Matthew Shepard, to how heterosexuality is reproduced at the 4-H Club, to a look at sexual encounters at a truck stop, to a queer reading of TheWizard of Oz.A journey into an unexplored slice of life in rural America, Queering the Countryside offers a unique perspective on queer experience in the modern United States and Canada
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".