Bibliographic record
Abstract
Unlike other Jewish memory foods such as homemade gefilte fish or matzoh ball soup, blueberry buns are virtually unknown to Jews living outside of Toronto. Yet these sweet, yeasty baked goods are a well-loved treat that trigger memorial narratives for those who remember eating them in downtown Toronto between the 1930s and the 1950s. For those who grew up during that era, blueberry buns represent childhood, summertime and visits with friends and family. This paper will explore the cultural significance of blueberry buns, as well as attempt to solve several mysteries that surround this Toronto treat: where did the recipe come from? Why did the buns become so popular? And finally, why have these treats remained solely within the boundaries of Toronto? Resume Contrairement a d'autres mets appartenant a la memoire collective juive, comme le poisson gefilte ou la soupe aux boulettes de pain azyme maison, les brioches aux bleuets sont pratiquement inconnues de la communaute juive a l'exterieur de Toronto. Ces pâtisseries au levain sont une gâterie appreciee qui declenche un flot de souvenirs chez ceux qui se rappellent en avoir mange au centre de Toronto dans les annees 1930,1940 et 1950. Pour tous ceux qui ont grandi a cette epoque, les brioches aux bleuets representent l'enfance, l'ete et les visites aux amis et a la famille. Cet article etudie la signification culturelle des brioches aux bleuets et tente de lever quelques-uns des mysteres entourant cette gâterie propre a Toronto : la provenance de sa recette, le secret de sa popularite et la raison pour laquelle elle est circonscrite a Toronto.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".