CANADIAN GHOSTS AND THE WILL TO TRUTH: READING MARLENE NORBESE PHILIPS’ LOOKING FOR LIVINGSTONE
Bibliographic record
Abstract
While the ghost may be a device for resolving past issues in literature, its presence in the archive is central to Derrida’s critical approach in Archive Fever. Presenting this paper at an international colloquium “Memory: The Question of the Archives” at Freud’s own archive, Derrida considers Yerushalmi’s dialogue with the ghosted Freud as the desire that drives the archive: “… hauntedness is not only haunted by this or that ghost,… but by the spectre of the truth which has thus been suppressed” (Derrida 1998: 87). For Derrida, truth is a trace as elusive as “ash,” untouchable but always recognizable in its absence, enforcing the Freudian trust in memory as true in part, the search for which, Derrida claims, inspires a sort of illness; thus, the fever of the archive. Derrida recognizes that remembering and repeating are central to the archive as an injunction to bear witness to the past which, according to Derrida, is a responsibility not to those who have passed,but for those who will read in the future.1 Nietzsche’s understanding of the will to truth as that which perpetuates the assumption that truth exists can be understood as implicit to the endlessly repeated aporia of Derrida’s ghost (Nietzsche 1956: 288). This spectre is made visible by the will to truth of a witness for specific future time and place.
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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 | 0.013 | 0.021 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".