La enseñanza-evaluación integrada de la oralidad reflexiva en las situaciones de aprendizaje de lectura entre pares en la enseñanza primaria y secundaria
Bibliographic record
Abstract
En un trabajo anterior se describió el primer objetivo de esta investigación que consistía en extraer las características lingüísticas de las conductas de justificación en los círculos de lectura entre pares (Hébert-Lafontaine, 2013). Aquí se describen los otros dos objetivos de la investigación: a) experimentar la enseñanza explícita de la expresión oral reflexiva en integración con la lectura lite-raria y b) analizar/comparar, en un estadio preliminar, los efectos de una enseñanza de este tipo sobre la capacidad de reformular su discurso por parte de alumnos de los últimos años de enseñanza primaria (10-12 años) y de la secundaria media (13-14 años), los cuales han discutido una misma novela y se han beneficiado de la misma enseñanza en expresión oral.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".