La educación inclusiva en Latinoamérica, El Caribe y el caso de Ecuador
Bibliographic record
Abstract
En este articulo se presenta un resumen analitico del diagnostico que hiciera el Banco Mundial en conjunto con la Canadian Association for Community Living, que se denomino: Educacion inclusiva en Latinoamerica y El Caribe Diagnostico actual y desafios para el futuro correspondiente al ano 2006, en cuyos analisis se imbrican los resultados de los paises participantes de los talleres y seminarios internacionales sobre esta tematica; entre los que se encuentran: Brasil, Argentina, Uruguay, Paraguay, por Centroamerica Nicaragua, El Salvador, Honduras, Costa Rica y Panama, en cotejo con el caso de la educacion inclusiva en Ecuador. En lo metodologico, se analizaron los resultados del diagnostico; los cuales se sustentan en los resultados de la investigacion y de estudios de caso de los paises con datos proporcionados por personas con discapacidad, familias, organizaciones de personas con discapacidad, maestros y autoridades educativas de escuelas publicas y privadas. A los fines de poder realizar esta empresa, se reviso el referido informe y otras fuentes bibliograficas, donde se exponen los casos de los paises participantes en el evento de modo que pueda cotejarse con resultados de otros anos posteriores. Puede referirse como una conclusion que: Es preciso lograr que los gobiernos disenen, elaboren y desarrollen politicas publicas que promuevan la educacion inclusiva. Estas politicas deben garantizar el derecho a una educacion de calidad de todas las ninas y ninos sin importar su religion, cultura, lengua, nivel socioeconomico, etc.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".