Embodied Genetics in Science-Fiction, Big-Budget to Low-Budget: from Jeunet’s Alien: Resurrection (1997) to Piccinini’s Workshop (2011)
Bibliographic record
Abstract
Abstract The article uses and revises to some extent Vivian Sobchack’s categorization of (basically) American science-fiction output as “optimistic big-budget,” “wondrous middle-ground” and “pessimistic low-budget” seen as such in relation to what Sobchack calls the “double view” of alien beings in filmic diegesis (Screening Space, 2001). The argument is advanced that based on how diegetic encounters are constructed between “genetically classical” human agents and beings only partially “genetically classical” and/or human (due to genetic diseases, mutations, splicing, and cloning), we may differentiate between various methods of visualization (nicknamed “the museum,” “the lookalike,” and “incest”) that are correlated to Sobchack’s mentioned categories, while also displaying changes in tone. Possibilities of revision appear thanks to the later timeframe (the late 1990s/2000s) and the different national-canonical belongings (American, Icelandic-German- Danish, Hungarian-German, Canadian-French-American, and Australian) that characterize filmic and artistic examples chosen for analysis as compared to Sobchack’s work in Screening Space.1
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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 | 0.001 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".