Bibliographic record
Abstract
In American society, rural spaces – particularly those of the working class – are seen as stagnant holdovers from a temporal past that “modern” society has evolved beyond. As a result, working-class rurality and those living within these places are viewed as static, ignorant, insular and so on: whatever places do not conform to the appearance of “modern” progress and development simply must be regressed, on both socioeconomic and cultural levels. While scholars in some disciplines are attempting to redress this misconception, other disciplines (like literary studies) largely align with the mainstream perspective that rurality represents a regressed past to our evolved present. However, despite the critical lack of attention to rurality as a viable space in the present, we can see in various fictional works that working-class rural spaces can effectively show us the interrelationship of rural spaces with “modern” society and culture in the present, the continuing relevance and deep history alike of said spaces, and the potential of these fictional working-class rural places to confront America's norms of progress and development within and without their fictional borders. Richard Russo's fiction illustrates the potential to bring out this critical working-class rural voice. Russo's fictional treatments afford the reader an opportunity to witness the ever-changing complexity (not the temporal and cultural regression) of working-class rurality. In turn, Russo's fictional working-class rural spaces offer a counterperspective to the mainstream (defined here as middle-class and (sub)urban) notions of progress that otherwise dismiss these perspectives. In his book Empire Falls , Russo uses nostalgia to assert this counterperspective. This nostalgia not only reaffirms the postwar and early twenty-first-century working-class rural identity of Empire Falls, but it also offers a critique of dominant conceptions of progress and development that continue into our present.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".