Do Androids Dream of Bad TV?: Un/originality in Neil Burger’s Voyagers
Bibliographic record
Abstract
Critics did not take kindly to Neil Burger’s Voyager (2021). On Rotten Tomatoes, the film scored a dismal 25%, and the consensus is that it’s a trip best not taken: “It has a game cast and a premise ripe with potential, but Voyagers drifts in familiar orbit rather than fully exploring its intriguing themes.” This article seeks neither to reclaim the film as an unjustly neglected cinematic masterpiece nor to assert its importance in the canon of dystopian works. Rather, it treats Voyagers as a test case for exploring our own critical investment in the genre. Our aims are twofold. First, we argue that the film speaks to the dystopian genre’s fundamental distrust of future generations to make the best decisions. It effectively exposes the central irony that we presume to know best though we had signally failed to do right by our planet in the first place. Secondly, we reveal how unoriginal work can still point to new ways forward. By the end of the film, the Humanitas mission is back on course, following Zac’s (Fionn Whitehead) demise. Sela (Lily-Rose Depp) is surely right to wonder, to Christopher (Tye Sheridan), how they should ensure that mutiny doesn’t recur. The short answer? They can’t—and they probably shouldn’t. The capacity for events, like those we witness in Voyagers, to recur—and many times over too—is at least partially responsible for the dystopian genre’s appeal and it contributes to the genre’s persistent ethical ruminations. This essay advances scholarship by suggesting that even the most derivative of cinema can offer profound insights into our world, in this case, how democracies work.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| 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".