Review: <i>A Place at the Nayarit: How a Mexican Restaurant Nourished a Community</i>, by Natalia Molina
Bibliographic record
Abstract
Book Review| August 01 2023 Review: A Place at the Nayarit: How a Mexican Restaurant Nourished a Community, by Natalia Molina Natalia Molina. A Place at the Nayarit: How a Mexican Restaurant Nourished a Community. Oakland: University of California Press, 2022. 312 pp. Illustrations. Hardcover $29.95. Jeffrey M. Pilcher Jeffrey M. Pilcher JEFFREY M. PILCHER is a professor of history at the University of Toronto and author of Planet Taco: A Global History of Mexican Food (2012). jeffrey.pilcher@utoronto.ca Search for other works by this author on: This Site PubMed Google Scholar jeffrey.pilcher@utoronto.ca California History (2023) 100 (3): 114–116. https://doi.org/10.1525/ch.2023.100.3.114 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Jeffrey M. Pilcher; Review: A Place at the Nayarit: How a Mexican Restaurant Nourished a Community, by Natalia Molina. California History 1 August 2023; 100 (3): 114–116. doi: https://doi.org/10.1525/ch.2023.100.3.114 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentCalifornia History Search Accessibly written and full of personal and scholarly insights, this book fulfills the promise of its subtitle, describing a diverse community centered around Los Angeles’s storied Nayarit restaurant. The “place” in the title is likewise aptly chosen, referring not only to the restaurant’s booths and workstations but also to the place-making and place-taking of customers and employees as they made a home for themselves and claimed their right to the city. Natalia Molina’s social history of a restaurant complements scholarship dedicated to political and union organizing by portraying the “many other ethnic Mexicans who did not fight for civil rights or decent labor conditions but still sought dignity and belonging in the country in which they settled” (19). The book is first a family history focused on the restaurant’s founder, Natalia Barranza, an immigrant from Mexico’s Pacific coast state of Nayarit and the author’s grandmother. Arriving in Los Angeles in... You do not currently have access to this content.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.049 | 0.045 |
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".