Waitin' on the Ghost of Tom Joad: The Neoliberal Reconstruction of the Great Depression Years in Cinderella Man
Bibliographic record
Abstract
This paper intends to examine the political rationality of neoliberalism through the Depression Era film Cinderella Man (Ron Howard, 2005). While neoliberalism has been widely mapped out, critiqued, and debated in a host of academic disciplines, the myriad forms American film has articulated, represented, and integrated neoliberal narratives remains a largely understudied issue within the field of cultural studies. The present contribution addresses, through a close filmic analysis, the set of discursive strategies by which neoliberalism reenacts and renarrativizes previous ideological, political, and cultural heritages. I argue that Cinderella Man ‘neoliberalizes’ the Great Depression, highlighting individualism and resilience while totemic questions such as class identity, the legitimacy of deregulated capitalism, and the specific causes and origins of the Depression are rendered either invisible or peripheral. Taking the notion of Gramscian hegemony as the overarching theoretical principle, I draw on a variety of theorists that have inquired into the underpinnings and logics of neoliberal thinking —namely Wendy Brown (2016), Pierre Dardot and Christian Laval (2014), and David Harvey (1990). Thus, the aim of this article is to analyze Cinderella Man as a neoliberal filmic text which significantly departs from the normative ideological, political, and cultural imaginaries historically associated with the Great Depression.
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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 | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".