Bibliographic record
Abstract
Mr. Vargas talks about what his life was like growing up in México; he remembers that the bracero program was greatly publicized in his hometown of Rodeo, Durango, México; in order to enlist, he traveled to the contracting center in Empalme, Sonora, México by cargo train; he waited for fifteen days with several thousand other men for their names to be called; they were often solicited by people from town to help pick cantaloupe and watermelon, but if they left, they risked losing their place in line and their chance at a contract; from there, he took another train to the reception center in the United States, where he was medically examined and deloused; as a bracero, he worked in the fields picking celery and lettuce; he goes on to detail housing, accommodations, amenities, provisions, treatment, payments, remittances, friendships and recreational activities; in addition, he explains that many men arrived thin, but with the food they ate, they left rather plump; one of his boss’s wives was involved with a church that gave religious English classes, but the men were not required to attend; while he was away, he sent letters, money and photographs to his mother so she would know he was fine; upon returning home, he often brought gifts for his family, including electric shavers, coats and dresses; sometime later, he married in Durango, México and eventually began raising a family; he was ultimately able to legally immigrate to the United States; overall, he has positive memories of the program, and he is proud to have been a bracero.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".