Code-Switching, Queering Food and Narrative Construction in Monica Meneghetti’s Memoir <i>What the Mouth Wants</i>
Bibliographic record
Abstract
ABSTRACT This article examines the extent to which the Italian-Canadian queer writer Monica Meneghetti, in her memoir What the Mouth Wants, challenges and disrupts heteronormative notions of gender and sexuality through the code-switching of food terms in Italian or in a Northern Italian dialect. Code-switching is used primarily to evoke memories of Meneghetti’s late mother through the author’s favourite dishes, and of the homophobia (or rather biphobia) directed at her by her father, with whom she used to make fresh pasta and cook Italian meals. The memories and flashbacks, interspersed with present-day accounts of the preparation of Italian childhood meals with her polyamorous family, allow the memoir’s protagonist to build a new sense of family: a queer Italian-Canadian family. Drawing on feminist and queer food studies, the article reveals that Meneghetti uses code-switching to signal point of view and to construct the memoir’s characters and plot, as code-switched food items are also linked to the notion of memory and to what it means to write the memoir.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.040 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".