Bibliographic record
Abstract
Abstract This article argues that Elysium communicates a ‘critical dystopia’ that illuminates and interrogates global capitalism’s worst social, political, ecological and technological conditions and shows them being resisted and changed, for the better. To this end, our article’s first section contextualizes Elysium by building upon recent studies of global Hollywood, the genre characteristics and politics of science fiction films and ‘critical dystopia’. The second section interprets Elysium’s dystopian future of society, the state, environment and technology, and argues it forwards a critique of present-day global capitalism’s class divisions and dispossessions, neo-liberal security state, ecological catastrophe and militarized technology. The third section excavates Elysium’s alternative to the fictional and actual dystopic conditions of capitalism the film critiques, thereby liberating the film’s imminent utopian content from the cage of its commodity form. The conclusion addresses some important criticisms of Elysium’s politics: its perpetuation of Hollywood’s ‘white saviour’ trope, regressive gender dynamics, and ‘single point of failure’ fantasy. Despite these problems, Elysium still has value as a critical dystopian film.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".