‘And Yet, What Would We Be Without Memory?’ Visualizing Memory in Two Canadian Graphic Texts
Bibliographic record
Abstract
Abstract Since “we live in a culture of confession” (Gilmore 2001: 2; Rak 2005: 2) a rapidly growing popularity of various forms of life writing seems understandable. The question of memory is usually an important part of the majority of autobiographical texts. Taking into account both the popularity of life writing genres and their recent proliferation, it is interesting to see how the question “what would we be without memory?” (Sebald 1998 [1995]: 255) resonates within more experimental auto/biographical texts such as a graphic memoir/novel I Was a Child of Holocaust Survivors (2006) by Bernice Eisenstein and a volume of illustrated poetry and a biographical elegy published together as Correspondences (2013) by Anne Michaels and Bernice Eisenstein. These two experimental works, though representing disparate forms of writing, offer new stances on visualization of memory and correspondences between text and visual image. The aim of this paper is to analyze the ways in which the two authors discuss memory as a fluid concept yet, at the same time, one having its strong, ghostly presence. The discussion will also focus on the interplay between memory and postmemory as well as correspondences between the texts and the equally important visual forms accompanying them such as drawings, portraits, sketches, and the bookbinding itself.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".