«Saving Metropolis»: body and city in the «Metropolis» tales
Bibliographic record
Abstract
The image of the destruction of the city has a long history, and resonates disturbingly with current events. It seems to question the very possibility of creating an architecture – that is, of giving the world a form and thereby a meaning. This thesis charts mutations of that imagery as it emerges in three visual narratives punctuating the last century: the "Metropolis" tales. These are Fritz Lang's film of 1926, Tezuka Osamu's manga or graphic novel of 1949, and the 2001 work of anime or Japanese animated film by director Rintarô. Despite their differences, these tales exhibit a fundamental overlap of concern: each deals in its own way with crises in modern conditions of life, crises articulated not only in the imagery of the city but also in that of the broken bodies central to it. The thesis argues that this imagery, hovering at the brink of and ultimately passing beyond the line of apocalypse, articulates an undiminished human yearning to engage in a life project. In our time this yearning, this desire, takes on a new form in which the city and the body adopt a precarious and problematic relationship to their image. But perhaps the seeming instability of this condition as articulated in disrupted bodies and cities is a more faithful reflection of the fundamental human anxiety reflected in myth, and the more foundational destructuring involved in our perception and making of the world, than any whole and healthy body, than any utopia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".