“Why shouldn’t the flâneur be stoned”: Anglo-Quebecois writer Gail Scott’s Turn-of-millennium Novel _My Paris_
Bibliographic record
Abstract
This talk offers a slice of my ongoing book project “Imperfect Flâneurs” (in contract with McGill-Queen’s UP) which studies reïnterpretations of the flâneur in contemporary novels. Baudelaire sketches the perfect flâneur as a cosmopolitan spectator who feels everywhere at home and sees the world from the privileged position at the centre. My project emerges from this simple question: can the flaneur be imperfect? My example for the talk is Gail Scott’s 1999 novel My Paris – a fictional travel journal of the writer who won a six-month residency with studio space in Paris. Like many travellers and sojourners in Paris today, during her stay, the narrator is tempted to taste the pleasures of walking Paris as a flâneur. Her daily flânerie leads her to this unexpected question with a street slang in the predicate, “why shouldn’t the flâneur be stoned[?]” I propose an innovative reading of this novel by way of critical reflection on this rhetorical question. The profound implications behind it are relevant to Scott’s creative process and such unprecedented features in this novel as the conversion of most of the verbs into present participles and the fabrication of a narrative voice that can be described as porous and sutured.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".