Bibliographic record
Abstract
This thesis explores two sets of relationships: “mother tongue”/second language and mother/daughter. \nMy novel acts these out simultaneously: my main characters are a mother and a daughter and the tensions between them are played out in their relationship with language, one a firm Anglophone, the other having ‘converted’ to French. The novel is primarily set in Montréal, which is, as Sherry Simon argues, a ‘divided’ space. Mostly Francophone but with a significant Anglophone community, it is a site of encounters, tensions, cohabitations; but most of all, a site of translation. As such, the setting feeds and reflects the dialogue between mother and daughter: the tensions that arise, the common ground they seek. Both of their voices appear on the page as they share their stories with each other. \nAs a French national, living in England and writing in English about a predominantly Francophone province and city, I am actively questioning the relationship between mother tongue and second language. My unique creative position is what prompted my research into language and translation. \nMy critical project offers an unprecedented analysis of two contemporary Québécois texts, The Girl Who Was Saturday Night by Heather O’Neill and Blanc dehors by Martine Delvaux. These texts are concerned with all kinds of languages: English and French but also silence. These languages share the page, which becomes a site of both conflict and reconciliation. These novels also explore tension-ridden mother/daughter relationships. In an interview I conducted with her, Lori Saint-Martin spoke of the need to negotiate a mutuality between mother and daughter. She also speaks of the importance of a dialogue that appears on the page. This is where the strands come together: my thesis explores encounters on the page, how languages cohabit, how mothers and daughters interact within one creative piece.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".