Where Is Holden Caulfield? The Catcher in the Rye : le potentiel d’une traduction « en québécois » suivi de la traduction de quelques nouvelles de J. D. Salinger
Bibliographic record
Abstract
Jerome David Salinger’s best-seller The Catcher in the Rye provoked controversy in the United States as soon as it was published in 1951. The loudest objections concerned its raw, obscene and blasphemous use of language. In the first section of this Master’s thesis, I bring forward a detailed analysis of the two most criticized elements of the novel’s language, the use of swearing and slang, based on a sociocritical reading of Catcher. Thus I attempt to explain the controversy. I then emphasize translation solutions conveying the original text’s subversive dimension by comparing the sociolinguistical contexts of the United States and Québec. I more specifically explore the potential of a reactualisation of the Québécois vernacular used in a heterogenous manner in the translation. I study the particular similarities between swearing and the use of “sacres/jurons” as well as the use of slang and what I call “la langue de Brébeuf,” characterized by the use of Frenglish. By doing so, I point out the ideological and esthetic aim of a translation project that I deploy in the second and last section of this Master’s thesis. In that section, I offer the translation of four short stories by J. D. Salinger, linguistically and thematically linked to Catcher: “Last Day of the Last Furlough,” “A Boy in France,” “This Sandwich Has No Mayonnaise” and “The Stranger.”
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".