Bibliographic record
Abstract
The work of Canadian cartoonist Seth positions itself between history and memory, and in doing so gives rise to a range of ambivalent impulses, chief among them an ambivalent longing for the past. Seth suggests that “the whole process of cartooning is dealing with memory,” and by consistently drawing attention to the narrative representation of the past, his comics reveal the extent to which the making of history is an act of great artifice. In its exploration of what Walter Benjamin calls “the mysterious work of remembrance—which is really the capacity for endless interpolation into what has been,” Seth’s work exhibits a complicated nostalgia, well aware of its own reactionary, restorative and nationalistic inclinations and able to channel them toward productive ends. Seth’s ironic, humorous and metafictional approaches to memory, remembrance and longing for the past reveal that his attitude toward these closely related subjects is deeply ambivalent. He nimbly mobilises history, (auto)biography, anecdote, documentary and other parallel modes. This investigation seeks to understand the ways in which his appropriation of such historicising discourses substantiates the powerful evocations of longing, loss and memory that characterise his fiction. Memory is here conceived not just as an invisible, ubiquitous mental phenomenon that reflects our experience of time and relation to the past, but as a medium, an art – and one which is in many ways akin to Seth’s mode of expression. The fundamental operation of comics, as a visual medium, initiates and makes space for narrative interpolations in a way that is not only comparable to but in a certain sense mimics the historical interpolations of memory; in both cases, longing is spurred by incompleteness. Seth turns the medium of memory on itself, using it as an instrument to examine the processes of remembrance and making history.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.065 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".