Bibliographic record
Abstract
En este taller identificaremos algunos de los rasgos principales que caracterizan el español coloquial latinoamericano y cómo estos se pueden incorporar en la clase de E/LE. Las actividades aquí presentadas se pueden incluir de manera individual en un curso de E/LE o como un conjunto de tareas relacionadas. Las actividades se diseñaron para un grupo de estudiantes norteamericanos de un nivel intermedio/alto (B2) en E/LE. Las tareas que presentaremos se han desarrollado asumiendo los siguiente: (1) el instructor de E/LE es un mediador que debe asistir en el proceso de la adquisición de la lengua de los estudiantes, por medio de la explicación de conceptos y facilitando actividades e información que ayuden a los estudiantes llegar a las conclusiones correctas. (2) Los aprendices son responsables de su propia adquisición de la lengua por lo que se espera altos niveles de iniciativa departe de ellos. Las actividades serán intercaladas con sesiones explicativas con el fin de que los estudiantes sepan en concreto los rasgos que deben buscar al analizar textos coloquiales.
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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".