Lo laboral en los Tratados de Libre Comercio entre países americanos
Bibliographic record
Abstract
En el contexto de los actuales procesos de globalizacion existen tres Tratados de Libre Comercio (TLC) en los que lo laboral forma parte de un Acuerdo de Cooperacion Laboral (ACL), acompanado de un Anexo que contiene “los principios laborales”: el TLC de America del Norte y su ACLAN, el TLC de Canada y Chile y su ACLCC, y el TLC de Canada y Costa Rica y su ACLCCR. Tambien hay dos TLC en los que lo laboral esta incorporado en el texto del Tratado: el de Estados Unidos de America y Chile (TLCEUACHI) y el de Estados Unidos, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua y Republica Dominicana (TLCEUACARD). En este articulo analizo los propositos, principios y compromisos laborales contenidos en esos TLC y ACL, interrelacionandolos con principios y normas de la OIT y con principios de caracter laboral adoptados en la ONU y la OEA. Concluyo formulando algunas consideraciones referidas a impactos de esos contenidos en las relaciones de trabajo. El articulo no se refiere a la globalizacion propiamente tal ni a los contenidos no laborales de los TLC. Tampoco examina lo atinente a sus contenidos institucionales ni a los procedimientos de verificacion del cumplimiento de obligaciones, solucion de controversias y aplicacion de sanciones.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".