Conexión tradicional: los vínculos mayas entre el altiplano de Guatemala y El Norte
Bibliographic record
Abstract
International migration constitutes one of the most significant phenomena impacting Guatemala today. About a million and a half Guatemalans live and work in rural and urban cities and towns across the United States and Canada. Like many other migrant groups, most Guatemalans sustain strong transnational linkages between their homeland and el norte (the United States). In the Guatemalan example highlighted in this article, such bonds owe much to the long-standing Guatemalan-U.S. historical connections, to the geographic proximity of the country to the United States. Drawing on ethnographic material, this article examines the divergent kinds of transnational connections that Maya indigenous (K´iche´) migrants craft and keep alive between their home community and their two primary destination localities in the United States—Houston, Texas and Los Angeles, California. The article shows the different means of communication and technology, as well as the varying types of transnational organizing —particularly grass-roots efforts— that help shape current linkages between those who go and those who stay. Keyword: Transnational migration, social ties, Guatemalan Maya migration, communications, grass-roots organizing.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".