A History-of-Mathematics Course for Teachers, Based on Great Quotations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Courses in the history of mathematics have been proposed based on great theorems and great problems (Journey Through Genius: The Great Theorems of Mathematics, 1990; Learn Math 6(1):31–38, 1986; Am Math Mon 99:313–317, 1992). Here we outline a course in the history of mathematics with “great” quotations as points of departure. These three “greats” have in common a number of important pedagogical features: they are interesting, they arouse curiosity, and they display, or lead to, important aspects of the mathematical enterprise. Moreover, the quotations (like the theorems and the problems) cajole, exasperate, stimulate, motivate, seduce, amuse – all welcome didactic traits. Perhaps more importantly, they are guideposts around which one may structure the development of a concept, a result, or a theory.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it