Bibliographic record
Abstract
Considering the importance of the Central American emigration like a social and economic phenomenon, this article makes a quantitative description about the population movements of each country from this region to the United States, principally using the information of these migrants in the last population census of this country, made in 2010. The article begins emphasizing the importance of the migrants, established like Latins or Hispanics, on each state of USA, classifying the states for the numbers of the migrant’s presence on each of them and also the growing number of migrants during the last intercensal period. Socioeconomic indicators are selected to compare the environment surrounding the migrants on each Centro American country before and after making the migrant movement, it means, the first conditions that surrounded them on their country and then when they move to the states of the USA, where emigrants of each Central American country are the majority among the Central American emigrants. These comparisons are made advising the reader not just about the restrictions of information, but also the conceptual differences that can hide behind the indicators and about the quality differences of getting the indicators in different countries. DOI: http://dx.doi.org/10.5377/pdac.v8i0.919 Revista Población y Desarrollo: Argonautas y Caminantes, Vol. 8, 2012 pp.51-75
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".