Schooling for "Deep-Knowing": On the Education of a Pithecanthropus Erectus
Bibliographic record
Abstract
We busted out of class, had to get away from those fools.We learned more from a three-minute record, baby, than we ever learned in school.Tonight 1 hear the neighbourhood drummer sound, I can feel my heart begin to pound.You say you're tired and you just want to close your eyes.And follow your dreams down.-from ''No Surrender" (Born in the USA) Bruce SpringsteenTwenty-five hundred years ago, Plato commented that the downfall of a city {polls) would result from the corruption of its tragedies.Tragedy, originally a "goat song" {tragodia) or sacred hymn performed at the festivals of Dionysus, god of wine and ecstasy, was the highest form of art in the ancient world.In tragedy, the poet {poietes) or "maker" was the teacher of grown-up men in the same way that the schoolteacher {didaskalos) was with regard to boys.Here, the case of the ancient, tragic poet-teacher is instructive in our modern context, for where a modern-day schoolteacher might be said to be an historian {historikos), or one concerned with understanding "the real facts" of the world and of human society, in his Poet- SEAN STEEL is Sessional Instructor in the Faculty of Education at the University of Calgary. Schooling for "Deep-Knowing"HUMANITAS • 133
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".