Bibliographic record
Abstract
Mr. Castilleda briefly recalls his childhood and working in agriculture with his family; he crossed the border to work illegally in the cotton fields with his father when he was ten or twelve years old; he remembers that his uncles came as braceros and as soon as he turned eighteen he enlisted in the city of Monterrey; after enlisting, he went through contracting centers in Piedras Negras and Hidalgo, Texas; he remembers the medical exams they were put through; he worked in places like La Mesa and Big Springs, Texas, as well as in Tennessee and Arkansas, mainly on cotton and bean fields; while working as a bracero he got married in México and he explains that he sent money to his family; in addition, he remembers that the people from the different cities he visited were very nice to the braceros; after the contracts ended he went back to México and later came back with his family illegally; after some years he arranged his residency and now all of his children live in the United States as well; Mr. Castilledas concludes that the overall experience of being a bracero helped him and his family
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.005 |
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; both teacher heads agree on what is shown here.
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".