An Ethnographic Study of Edmonton Food Trucks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article develops an anthropological understanding of the intersection between food and culture in Edmonton’s food truck industry. More specifically, I explore how Edmonton food trucks are able to connect local and global cuisines and cultures through the menu items they offer and images they present to customers, which are predominantly influenced by local, ethnic, authentic and fusion creations. I gained data for this study by employing an ethnographic methodology and relational approach, which involved conducting semi-structured interviews with Edmonton food truck vendors and customers, and engaging in participant observation from May through August of 2019. The following food trucks serve as case studies in my research: Explore India, Dosi Rock, Dedo’s Food Truck and Catering, Meat Street Pies and The Dog. My findings reveal how advertising themes common to Edmonton food trucks, which include notions of authenticity, traditionalism and high quality ingredients, contribute to the construction of a cultural “Other” for customer consumption. In addition, my findings reveal how Edmonton food truck vendors are inspired to develop menus and dishes rooted in and inspirited by their cultural heritages, transnational identities, world travels and movement across ethnoscapes. In conclusion, I argue that the globally inspired ethnocultural cuisines offered by Edmonton food truck vendors are “localized” in a variety of meaningful ways. This study contributes to an underrepresented literature on street food vending in Edmonton by analyzing how food truck move through, occupy, and create urban spaces in meaningful ways.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it