Memories of the Future: Speculative Cold War Histories in Yosep Anggi Noen's The Science of Fictions and Daniel Hui's Snakeskin
Bibliographic record
Abstract
In 1965 Indonesia, the CIA helped Suharto spread false reports on a coup plot by the PKI (Partai Komunis Indonesia), contributing to an anti-communist purge; that same year, a farmer chances upon a film shoot by a foreign crew of a fake moon landing and has his tongue cut off. The latter is a speculative invention of Yosep Anggi Noen’s fiction film, The Science of Fictions (2019). In Daniel Hui’s hybrid speculative fiction / documentary Snakeskin (2014), set in the year 2066 in Singapore, references to the 1950s Chinese leftist movements form part of the film’s excavation of national myths and half-forgotten memories. Noen’s imagined past and Hui’s speculative future meet in Cold War secrecies that periodically haunt the cinema of the region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".