Meatpacking and the Transformation of Rural Communities: A Comparison of Brooks, Alberta and Garden City, Kansas*
Why this work is in the frame
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Bibliographic record
Abstract
A bstract North America's meatpackers have relied upon immigrants to staff their plants from the earliest days of the industry in the late nineteenth century when packinghouses were located in urban areas adjacent to stockyards. A hundred years later the industry remains dependent on an immigrant labor force, but now most of its plants are located in rural areas. This means rural communities are transformed with the arrival of immigrants to staff their plants. But Canada and the United States have different immigration policies, which means they draw upon different immigrant sources. Canada favors the recruitment of highly skilled labor while the United States emphasizes family reunification. This paper examines whether this difference affects the labor force composition of a Canadian and U.S. meatpacking plant, and the associated transformation of the plants' host communities.
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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 | 0.001 | 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 | 0.002 |
| 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