THE THEORY OF OBJECTIFICATION AND ITS PLACE AMONG SOCIOCULTURAL RESEARCH IN MATHEMATICS EDUCATION
Bibliographic record
Abstract
This article is an attempt at locating the theory of objectification (TO) among sociocultural research in mathematics education. The first part contains a summary of the emergence of sociocultural perspectives in mathematics education research. The second part deals with some of the central ideas that underpin the TO. It begins with a discussion of the concepts of teachers and students. Then, the general trend of language-centered types of theorizing in mathematics teaching and learning is discussed. The discussion is followed by a brief presentation of the concept of activity as understood in dialectic materialism. Such a concept is central to the TO. This concept, however, is reformulated as joint labor, which works in tandem with a dialect materialist concept of knowledge and the knower. Through these concepts the TO reformulates teaching-and-learning as an ethical cultural-historical phenomenon, providing the TO with a distinct orientation among sociocultural research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".