Alternate Endings: The Cold War Meets Neoliberal Television in <i>Counterpart</i>
Bibliographic record
Abstract
This article uses the example of the Starz television series Counterpart to suggest some preliminary hypotheses about the enduring appeal and important implications of telling “Cold War” stories through contemporary television. It draws on and contributes to historiographies of the postwar world, Cold War Germany, media history, historical memory, and recent work in critical media industries studies to explore a number of interrelated questions about the history, legacy, and representation of the Cold War, as well as the industrial conditions of contemporary television production and distribution. Counterpart, as I show, is a particularly keen example of television as both product and servant of neoliberal ideas, naturalizing the principles and also practices of neoliberalism for a transnational audience. It also exemplifies a new generation of television spy thrillers that is reimagining Cold War conflict and projecting a post-triumphalist version of the Cold War onto the problems of the post-9/11 world.
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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 | 0.005 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".