Análisis de caso de dos instituciones bilingües de la ciudad de Quito
Bibliographic record
Abstract
Bilingual Educational Programs have experienced a growing demand all over the world, there are many perspectives about how and when to introduce a second language in educational programs, but seems to be unquestionable the importance of giving second language skills in educational programs. Canada has documented and study their bilingual educational programs for decades, and there have been successful in their outcomes. In Ecuador there are more than a hundred bilingual private schools registered (Ministerio de Educación del Ecuador, 2011) but there isn’t enough information about what kind of programs they are offering and their outcomes. It is important to recognize and understand how bilingual education works and what to expect when our students are involved in that kind of programs, this study couldn’t find objective and reliable information about comparative outcomes and characteristics of the programs that are offering bilingual education in the Ecuadorian context. \nThe objective of this study is to understand how two different bilingual educational programs differ in their approach about second language instruction and how their outcomes are in the sixth grade of general education; our goal is not to compare but to get to understand each program and their outcomes. \nThis study pretends to be a reliable source of information for parents and teachers that are concerned about bilingual education outcomes. This study will review how two different programs of bilingual education are structured and work in the Ecuadorian context, their characteristics, objectives and outcomes.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".