'Culinary Memoirs.' Review of Culinary Landmarks by Elizabeth Driver and Butter Cream: A Year in a Montreal Pastry School by Denise Roig
Bibliographic record
Abstract
While these two books could not be more different in size and scope, they are both culinary memoirs of a kind that address a growing fascination with Canadian foodways and what they reveal about who we are. Neither one of these is a cookbook, although recipes do punctuate both. Elizabeth Driver's Landmarks chronicles 125 years of Canadian cookbooks in its 1257 pages, tipping the scale at about ten pounds (five pounds more than the maximum weight for my kitchen scale). Roig's is the memoir of one year spent completing the French pastry program at Montreal's Pearson School of the Culinary Arts. If Butter Cream is a memoir of a year in the life of a student and her classmates, Culinary Landmarks, like a memoir, chronicles the way Canadian cookbooks can best be understood in the context of their time and place, and the company they keep.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".