Imperial Vision in the Arctic: Fleeting Looks and Pleasurable Distractions in Barker’s Panorama and Shelley’s Frankenstein
Bibliographic record
Abstract
The early nineteenth century saw a rebirth of British arctic exploration and the enthusiasm inspired by these new, seemingly benign imperial endeavors spread quickly and thoroughly through the popular press. One of the most popular media for conveying the news and results of imperial projects was Barker’s panorama in Leicester Square. This medium encouraged a form of vision that was particularly conducive to garnering public support; the overwhelmingly large and meticulously detailed canvases caused the viewer to engage in a swift, haphazard form of looking that conveniently drew focus away from all the potential violations of people, landscape and property implied in exploration of regions such as the Arctic. Mary Shelley’sFrankenstein, published just before the exhibition of Barker’s first arctic panorama, presents a critique of this form of vision in the arctic frame narrative, which is plagued by Captain Walton’s continually distracted looks.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.020 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".