From Disincorporation to Rematerialization: <i> Breaking Bad</i> and the Life of Cash
Bibliographic record
Abstract
Global capitalism creates a culture of abstraction, described by Fredric Jameson as “a kind of cyberspace in which money capital has reached its ultimate dematerialization, as messages which pass instantaneously from one nodal point to another across the former material world.” The “becoming information” of money has been celebrated by technophiles like David Wolman who contends paper money is now largely the stuff of “crooks and terrorists.” And indeed, the capitalists at the centre of complex televisual crime sagas like Breaking Bad are continually frustrated by the recalcitrant materiality of their paper profits. Martin Shuster suggests that Breaking Bad amounts to a critique of Western science, specifically its tendency to “empty” the material world of meaning by prioritizing “instrumental” reason. I argue that the comical efforts of Walter White (the show’s chemistry-teaching, drug-manufacturing protagonist) and other characters to control the unruly materialism of cash represents this failure of instrumental reason, whether expressed in chemical equations or prices, to achieve fully the “dematerialization,” or what White calls the “disincorporation,” of the world. Ultimately, the unmanageable corporeality of money allegorizes the persistence of non-capitalist, material desires in mass cultural products like Breaking Bad.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".