Sonic Spectres: Word Ghosts in Madeleine Thien’s Dogs at the Perimeter and the Digital Map Project, ‘Fictional Montreal/Montréal fictif’
Bibliographic record
Abstract
This article analyzes various ghosts and their connections with the unsaid and said in relation to Madeleine Thien’s Dogs at the Perimeter (2011) and the digital map project, ‘Fictional Montreal/Montréal fictif’ (Morgan and Lichti, 2016–17). Drawing on Jacques Derrida’s work on spectres, it suggests that Thien’s novel offers both negative and positive hauntings, by drawing attention to the far-reaching effects of the Cambodian genocide. It goes on to reflect on absence and presence, voice and body in relation to the digital map, which features recordings of authors reading extracts of their fiction set in Montréal. Arguing that ‘Fictional Montreal/Montréal fictif’ performs an interplay between material and imaginary geographies, the article proposes that the map offers the possibility of new conceptualizations of Montréal. In so doing, it argues that both it and Dogs at the Perimeter embrace the potentially utopian aspect of spectrality identified by Derrida. This is due to their encouraging readers to think about our collective responsibilities to each other in a world characterized by mobility and migration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".