Bibliographic record
Abstract
RESUMEN: ¿Cuáles son las razones que han favorecido un tratado de libre comercio en América del Norte? El artículo sugiere algunos de los intereses políticos y económicos inmersos en la negociacián. Como Canadá ya tiene su propio acuerdo con los Estados Unidos, su objetivo fundamental será evitar que México logre beneficios que pudieran perjudicarle. Para México, por su parte, el tratado puede ser la alternativa para recuperar el crecimiento económico, mientras que para Estados Unidos es una opción para mantener su competitividad frente a Europa y el Sudeste Asiático, y para reorientar sus relaciones con América Latina.ABSTRACT: Which are the reasons that are leading to a free-trade treaty in North America? The article suggests some economical and political interests involved in the negociation. As Canada has it's own agreement with the US, it would try to be ahead of Mexican benefits in the dkaL From Mexico's viewpoint, the treaty may be the alternative to restore economical growth, and for the US, it could be an option to mantain it's competitiveness against Europe and Southern Asia, and to reorientate it's relations with Latin America.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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; 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".