Knowledges Exchange as a Framework for the Scholarship of Teaching and Learning
Bibliographic record
Abstract
In western society, the so-called traditional education system is based on an Industrial Age model that was developed several hundred years ago.At that time, its purpose was to provide mass education, with a focus on teaching the "3 Rs" to children and youth as preparation for running factory machinery.Society has moved beyond the Industrial Age, yet the same educational paradigms persist.This essay is founded on the proposition that a new framework for education is needed for the 21 st century, based on the concept of Knowledges Exchange.By posing a series of questions, and exploring some of the possible answers, it is hoped that educators will be encouraged to re-consider some of the existing norms of the education system, and adopt alternative approaches in their practice.Those who want to engage in discussion about the issues raised here may wish to contribute to Elizabeth's blog at: http://knowledgesexchange.wordpress.com/
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 | 0.029 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.015 | 0.139 |
| Scholarly communication | 0.028 | 0.038 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".