Quantum Learning: Learn Without Learning
Bibliographic record
Abstract
Quantum Education is the natural way to learn---motivating and exciting people to take responsibility for their own education.. The Montessori Model represents the closest example of Quantum Education, where the environment is prepared with didactic materials for the children to absorb at their own pace. Where children learn without formal pedagogical machinations, without consciously learning how to learn---by doing. Like Quantum Logic or Quantum Physics or Quantum Games, quantum thinking is an insightful, body/mind approach, attempting to connect our classical worldwhere objects or things have definite identitieswith our new quantum worldwhere things take on multiple realities simultaneously. The concept of mind, limiting our perceptual abilities is no longer confined to the brain or even the body---all organs are, in some ways, thinking organs, permitting restructuring of our cognitive educational commitment toward infinite choice and possibility. Quantum Education has been defined by the Canadian Quantum 2000 Group as the need for a quantum shift in what students are expected to learn in Alberta public schools starting Y2000.
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.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.008 | 0.018 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".