Lake Effect Pizza: The Commodification and Culture of Pizza in Toronto, Ontario and Buffalo, New York 1950-1990
Bibliographic record
Abstract
This dissertation examines the history of pizza in Toronto, Ontario and Buffalo, New York, spanning a period from 1950 through to the early 1990s. Pizza, far more than its constituent parts of dough, sauce, and cheese, is used as a lens to explore the history of immigration, business, labour, urbanization, gender, culture, economics, consumption, and food in Toronto and Buffalo. Through an analysis of a variety of sources, including oral interviews, GIS-produced maps, and newspapers, this dissertation explores how pizza was commoditized as an item of popular urban consumption and culture, in a variety of sites and spaces within the cities. \n \nThe commodification of pizza, the development of pizza industries, and the culture of consumption in Canada and the United States paralleled currents in postwar life in Toronto and Buffalo. The central question emanating from these histories and which is explored here is the ways in which culture, ethnicity, immigration, and urban economies shaped the commodification of an ethnic food. Pizza was once confined to the foodways of Italian immigrants in Canada and the United States, but was eventually commoditized for sale to non-Italians. The commodification of the food item spread from small family owned businesses attributed to Italian ethnic economies to franchises and conglomerates owned by non-Italians. Moreover, the food item itself was modified based on availability of ingredients and to appease the taste preferences of non-Italians. \n \nThe Great Lakes cities, Toronto and Buffalo had similar sized populations, patterns of Italian immigration, industry and growth in 1950. However, by 1990, Toronto was the largest city in Canada, a multicultural metropolis with strong economic output, and Buffalo was a regional American city, which suffered greatly from deindustrialization and protracted population loss. Despite similar postwar currents, the staggering divergences between the economic capacities of two urban centres shaped different patterns of commodification and consumption of pizza.
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 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 | 0.004 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".