Take Me Back to the Ball Game: Nostalgia and Hegemonic Masculinity in Field of Dreams
Bibliographic record
Abstract
The financial and critical success of the film Field of Dreams attests to the wideranging appeal of its main character and the nostalgic ideals he embodies. One critic exclaims that “Field of Dreams soars beyond dreams” and describes the film as “a fantasy about belief, hope, fathers and sons, passion for life. A masterwork of wonderment,” while another describes it as “a magical movie. It’s so perfect, it’s like a miracle—a completely original and visionary movie.”1 Wes D. Gehring argues that Field of Dreams is a “populist” film in the tradition of Frank Capra, for like populism the film celebrates “adherence to traditional values and customs (mirroring the phenomenon’s [populism’s] strong sense of nostalgia)” and a “general optimism concerning both man’s potential for good and the importance of the individual” (36). And Caroline M. Cooper, citing an interview of Bill Clinton by Tom Brook, explains that Field of Dreams is, after High Noon (1952), the favorite film of President Clinton. He loves it, apparently, because of its message that “if you build it, they will come”; he finds it a “fabulous fairy tale” which “makes people feel that anything can happen.”
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.051 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| 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".