Cannibalism, Charles Dickens, and Franklin’s Last Arctic Expedition: “a fate as melancholy and dreadful as it is possible to imagine”
Bibliographic record
Abstract
The absence of the figure of the cannibal in The Frozen Deep is central to this study that investigates Dickens’s representation of the fate of Frank- lin’s 1845 Arctic expedition “contrapuntally” (Said 1994: 59) by focusing on his dialogic exchange with Dr. John Rae that is at the origin of Dickens’s House- hold Words articles. Furthermore, it contextualises Dickens’s defence of Franklin’s reputation within the Victorian colonial discourse of cannibalism, wherein the term “describe[s] the ferocious devouring of human flesh supposedly practised by some savages” (Barker, Hulme, Iversen 1998: 4), and intersects it with Rae’s representation of anthropophagy to outline how Dickens’s imperial narrative, based on “a static notion of identity” built on absolute difference “between Europeans and their ‘others’” (Said 1994 xxviii), relegated the Inuit’s story to the margins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".