Bibliographic record
Abstract
The science fiction films of Andrei Tarkovsky, Solaris (1973) and Stalker (1979), are complex responses to the repressive atmosphere of Brezhnev’s rule, after the 7-year delay in seeing Andrei Rublev (1971) released publicly. By using science fiction—a genre that Tarkovsky openly maligned—he was able to fly beneath the radar of State censorship, and develop a nuanced response to the application of Marxist theory of religion in the Soviet experience. Arguing in these films (and in others in his oeuvre) that humans still need the affective dimension of religion (though not the hierarchical, institutional elements of it that Marx had identified with sedation), Tarkovsky hid within his science fiction films a thoroughgoing critique of the Soviet application of Marx. This article uses the concept of “war machine” from the philosophy of Gilles Deleuze and Félix Guattari to analyze how Tarkovsky did this, and demonstrates that Tarkovsky’s engagement with Marx’s philosophy in these two films shares much in common with Deleuze and Guattari’s way of understanding human meaning making.
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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 | 0.000 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".