Tachyons, tactility, drawing and withdrawing: cinema at the speed of darkness
Bibliographic record
Abstract
Longitudinal, quantitative analyses of cinema have established how Hollywood is getting ‘quicker, faster, darker’. While in some senses the ‘intensified continuity’ of contemporary Hollywood narration is a given, the increased darkness of contemporary mainstream cinema remains unexplored – especially with regard to how its speed and its darkness might be inter-related. If to darken the majority of the screen during a film helps to draw our attention to the salient aspects of the image that are better illuminated, then of course this also allows for a faster cutting rate: in principle, there is ‘less’ information for the viewer to have to take in during each shot, meaning that the film can then cut to subsequent images more rapidly. However, there are other ways in which we can interpret this ‘darkening’ of contemporary film narration. For example, it perhaps ties in with a widespread sense of disorientation with regard to the increasingly globalized and connected world that digitization has helped to bring about, and which is equally reflected in the rise of the contemporary ‘mind-game’ or ‘puzzle’ film that is a staple of contemporary Hollywood. The darkness in such films thus gives expression to uncertainty and disorientation. More than this, though, we might use physics to understand the darkness of contemporary cinema in a more ‘meta-physical’ fashion. While it is accepted that light is the ‘fastest’ phenomenon in the known universe, there nonetheless remain unilluminated aspects of the physical universe that defy light as the limit of speed – and which convey the interconnected nature of matter in the contemporary universe. For example, polarized particles have been proven simultaneously to respond to stimuli – at a speed faster than it would take light to travel from one particle to the other, a phenomenon that baffled Albert Einstein, who referred to this process as ‘spooky action at a distance’. Not only does this process suggest what Karen Barad might refer to as the entangled nature of all matter, but it also suggests speeds beyond, or at least different, to that of light. In this essay, then, I shall theorise a ‘speed of darkness’ that can help us to understand how the darkening of contemporary cinema ties in with the interconnected, invisible (‘spooky’) and ultra-rapid nature of the digital world. Perhaps it is not in the light but in the darkness that we can identify the key to understanding contemporary mainstream cinema and the globalized, digital world that produces it.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".