Bibliographic record
Abstract
By ‘unearthing’ artefacts from folded layers of time, media archaeology undermines linear historical discourse: in this regard, this chapter addresses an exemplary art-based project on the origins of cinema that takes the epistemological metaphor of ‘excavation’ at its word. In 2011, the Canadian artist Henry Jesionka discovers several ancient bronze and glass objects on a Croatian beach, dates the pieces to the first century CE, and identifies them as components of an intricate Graeco-Roman mechanism for the projection of moving images. This rewriting of media history not only illustrates how traits of materiality and contingency interfere with teleological history; it also reflects on industrial capitalism’s paradox claims of ‘reason’ and the ideological presuppositions of progress: Cornelius Castoriadis’s notion of a merely simulated Rationality of Capitalism (1997) suggests that traditional narratives of technological invention are invariably organized around a clandestine and insufficiently repressed nucleus of the unforeseen, unpredictable, and irrational. By admitting to a similar element of chance or lost control, Jesionka’s Ancient Cinema project and new founding myth of cinema comment on the logic of media archaeology as an expression of late capitalism’s waning belief in its own rationale.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".