Dewey in Argentina: Tradition, intention, and situation in the production of a selective reading
Bibliographic record
Abstract
From the 1910s on, Argentinean educators looked repeatedly at Dewey’s work in search for models of educational reform. However, his undisputed reputation as a major thinker contrasted with a very selective view of his work and a weak reception in institutional terms. In fact, substantial parts of his scholarship were marginalized, in a selective reading that produced a de-politicized version of Dewey as an educational reformer. The multiple relationships between “democracy” and “education” or “schooling” opened up by Dewey’s thought were reduced in Argentina to a peculiar “didactics,” in a movement that reflected the intellectual and political trajectories of the supporters of the New Education Movement. In this chapter, working through translations, articles and comments on Dewey’s work, we will will focus on understanding the range of alternative readings that were available at a particular time, and the contexts of debate in which they became possible. The liberal and Catholic traditions of reading foreign references and models will be put together with the struggles that organized political oppositions in the period considered, and with the particularly heated climate (first democratically elected government, military dictatorships, Perón’s election) that marked these years and that tainted Dewey’s reception in Argentina.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".