The Cybernetic Information Dialectic
Bibliographic record
Abstract
Chapter 2 reads John Dos Passos’s U.S.A. Trilogy in the context of cybernetics theorists Norbert Wiener’s and Claude Shannon’s contradictory definitions of information (Wiener’s theories align the concept with pattern, while Shannon instead describes it as a measure of randomness). Love argues that Dos Passos’s trilogy integrates both sides of this opposition in ways that are important to our understanding of the cultural and political dimensions of early twentieth-century cybernetic thinking. Focusing on the novels’ “Newsreel” sections, she illustrates how this technology – in both form and content, as well as broader industry practices – epitomizes the logic of cybernetic information. By incorporating a literary version of this media form into his novels, Dos Passos demonstrates how predictable patterns jostle with random chance as catalysts for change and progress in the United States. This interdisciplinary pairing shows (a) how cybernetics theories can help us understand the ideological work that texts like Dos Passos’s novels and newsreel productions undertake, and (b) how modernist literature encouraged readers to develop strategies for cybernetic thinking.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".