MétaCan
Menu
Back to cohort
Record W7019352838

Food and Women in an Italian-Canadian Novel:
\nTenor of Love by Mary Di Michele

2023· article· en· W7019352838 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)Identity (music)Context (archaeology)Perspective (graphical)Value (mathematics)ImmigrationPleasureLegitimacy
DOInot available

Abstract

fetched live from OpenAlex

Food is an important “identity marker” and plays a key role in the migration process: by consuming the food and maintaining the culinary habits of their country, migrants affirm their identity and culture. Moreover, food is often associated with memory and nostalgia for the country of origin: indeed, it is evident that the presence of food and its preparation in literature becomes a kind of mirror for society. In the case of Canada, this analytical perspective appears particularly interesting, because its cultural context is hybrid: half American, half European, and with a considerable number of immigrants from all over the world.
\nIn this “gastro-literary” journey I propose to take, I will try to show that nourishment is a solid and real principle in the construction of identity in Canada, through the works of Italian migrant writers. In this contribution, I will analyze the theme of food connected to pleasure in a novel by an Italian-Canadian writer, Mary Di Michele, entitled Tenor of Love. I will mainly consider the passages in this novel in which culinary practices are used as metaphors for situations typical of Italian migrants to Canada. Thereafter, I will examine the close link between the search for identity and female authenticity present in the novel, and how Di Michele manages to deconstruct the clichésassociated with Italian culture and tradition through the figurative value of nourishment, managing to restore, through writing, legitimacy to women.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.045
GPT teacher head0.239
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCINECA IRIS Institutional Research Information System (University of Bari Aldo Moro)Same topicCulinary Culture and TourismFrench-language works237,207