Philosophy of Mathematics in the Classroom: ASPECTS OF A TRI-NATIONAL STUDY
Bibliographic record
Abstract
Introduction: The following papers were presented at a panel of the Interamerican Congress of Philosophy in Puebla, Mexico, in August 1999. The panel was convened by Dr Maria Teresa de la Garza of the Universidad Ibero Americana, who invited Dr Marie-France Daniel of the University de Montreal and Dr Christina Slade of the University of Canberra to discuss the teaching of Philosophy for Children adapted for mathematics. All three are participants in a Canadian government funded research project led by Dr Daniel, in which a program developed by Dr Daniel and her Quebecois colleagues, Dr LaFortune, Dr Pallascio and Dr Sykes, designed to teach philosophy of mathematics to childen is being tested in the original French, and in translation in English and Spanish. The round table discussion in Puebla was designed to introduce the program, and defend its place in the curriculum.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.024 | 0.011 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.008 |
| 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".