La inserción profesional docente en Quebec y en Colombia: ¿qué podemos compartir y aprender?
Bibliographic record
Abstract
Teacher Professional Induction in Quebec and Colombia: What can we share and learn?This paper makes a theoretical and problematizing exploration of the concept of Teacher Professional Induction in two social contexts: Quebec and Colombia.From a comparative perspective, we analyze this issue according to the regulations that early education teachers must comply with in these two contexts when entering the La inserción profesional docente en Quebec y en Colombia: ¿qué podemos compartir y aprender?En este artículo realizamos una exploración teórica y problemática del concepto de inserción profesional docente en dos contextos sociales: Quebec y Colombia.Desde una perspectiva comparativa, hacemos un análisis de este tema según los procesos normativos de ingreso a la profesión que viven los docentes de la educación básica en los dos contextos y las problemáticas a las cuales estos se enfrentan durante la búsqueda de su primer empleo como maestros.Finalmente, presentamos algunos de los dispositivos de acompañamiento implementados en Quebec.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".