Cinema, the (Digital) Machine of the Imaginary: Revisiting Edgar Morin in the Quest to Create a Theory of Cinema in the Digital Age1
Bibliographic record
Abstract
Digital image technology facilitates the production and distribution of images, and at the same time, instills doubt as to the integrity of those images. As a result, spectators today trust and doubt the image while still retaining a need to see a double of the world on screen. Edgar Morin’s work on cinema permits us to speak of cinema in the digital age because he recognizes that from its origins cinema has been a “mirror-machine” that reflects the spectator’s imaginary and practical relationship with images as experienced through new technologies. I will explore Morin and Christian Metz’s writings on cinema to analyze cinema’s foundational element : the ability to satisfy the besoin de cinéma throughout changes in technology. Cinema persists as digital moving images because by evolving technologically it responds to the spectator’s need to see a double of the world on screen in order to negotiate the demands of society and personal desires.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".