Bibliographic record
Abstract
The story of comics is also the story of the modern city. Visible Cities, Global Comics thus makes urban contribution to an interdisciplinary phase in comics studies. Striking a balance between descriptive, historical, analytical and theoretical modes, Fraser’s research monograph explores representations of the city in a selection of comics from across the globe. First, this book brings insights from urban theory to bear on specific comics texts; and second, it uses comics texts to elucidate themes of urbanism, architecture, planning and the cultures of cities in works from the 18th through the 21st centuries. Throughout, close readings of comics by artists from a range of locations—Argentina, Belgium, Brazil, Canada, China, England, France, Holland, Japan, Norway, Spain, Switzerland, the United States, and Uruguay—contribute to an exploration of larger urban themes. Chapters include “The Modern City Streets” (ch. 1), “The Passions of Everyday Urban Life” (ch. 2), “Urban Planning, Built Environment and the Structure of Cities” (ch. 3), “Architecture, Materiality and the Tactile City” (ch. 4), and “Danger, Disease and Death in the Graphic Urban Imagination” (ch. 5). Fraser’s writing presumes no previous knowledge of either urban theory or the ninth art. Readers are introduced to names, places, historical events, urban thinkers, and formal elements of the comics medium with which they may not be familiar. In the process, each chapter introduces readers to specific comics artists and texts and investigates a range of matters pertaining to the medium’s spatial form, stylistic variation, and cultural prominence.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".