Baking power: French-Canadian and Franco-Ontarian cultural identity as defined by evolving traditional foodways in Astorville, Ontario
Bibliographic record
Abstract
Questions about cultural identity and allegiance are complicated. What makes a person French, French-Canadian or Franco-Ontarian? What is the difference between these various labels? How do demographics, gender, and age impact the ways in which cultural allegiance is created, maintained, or discarded? What defines a person’s membership in a cultural group? Is it one’s ability to speak the language? To make and/or eat cultural foods? If one of these fails to be present, can the person still be a part of the group? In our multicultural country, and especially in rural communities in Northern Ontario where Francophones find themselves to be part of a minority, such questions do not have simple answers. Studying cultural retention in such communities necessitates paying attention to more than just who is speaking French and/or to who is an activist for French rights. It also requires understanding how individual attitudes and behaviours are like and/or unlike those of others and of the larger group. Foodways are one of the specific cultural practices that can tell us about the group. Indeed, traditional foods have been shown to be very political expressions of personal values and opinions. What power does French-Canadian food have over those who make it? What does it tell us about those who claim allegiance to this cultural group? This interdisciplinary case study of Astorville, Ontario, relates to the fields of food studies, cultural studies, history, gender studies, material culture studies, performance studies, and autoethnography. By studying foodways, which are closely connected to heritage, language, religious practices, and rituals, this project seeks to understand how minority groups resist and/or acquiesce to societal pressures to conform to the culture of the majority. Knowing that modernisation and urbanisation have changed the lifestyle of once agricultural communities, that women now participate in the workforce, and that an individual’s personal history is an important factor in determining how one subscribes to cultural norms, this is an important time to understand the cultural evolution taking place in communities, like Astorville, Ontario, where the French population has gone from a majority to a minority since it was established.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".