Algunos desafíos encontrados en la elaboración de la Teoría de la Objetivación
Bibliographic record
Abstract
Este artículo presenta una reflexión alrededor de algunos desafíos encontrados en la elaboración de una teoría de inspiración vygotskiana sobre la enseñanza-aprendizaje de las matemáticas: la teoría de la objetivación. Se discute el contexto histórico de donde emerge la teoría y las dificultades encontradas en concebir el aprendizaje no como un proceso subjetivo, como lo plantea el constructivismo, sino como un genuino proceso social-histórico-cultural. Se arguye que una de las dificultades más importantes de las aproximaciones socioculturales educativas contemporáneas reside en brindar una descripción teórica clara de la relación entre el individuo y su cultura. La respuesta de la teoría de la objetivación se encuentra en su concepto de labor conjunta.Some Challenges Found in the Elaboration of the Theory of ObjectificationThis article deals a reflection about some challenges encountered in the elaboration of a theory of Vygotskian inspiration about the teaching-learning of mathematics: the theory of objectification. We discuss the historical context from which the theory emerges and the difficulties encountered in conceiving learning not as a sub-subjective process, as proposed by constructivism, but as a genuine social-historical-cultural process. It is argued that one of the most important difficulties of contemporary sociocultural educational approaches lies in providing a clear theoretical description of the relationship between the individual and his culture. The answer of the theory of objectification is found in its concept of joint work.Handle: http://hdl.handle.net/10481/49438Scopus record and citation
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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".