Interview - Meta-Education: The Attempt to Get Beyond a Politicized Conceptual Framework in Philosophy of Education
Bibliographic record
Abstract
In this feature interview, Professor Nicholas Burbules talks with Professor Scott Johnston about his upcoming book, Meta-Education: The Attempt to Get Beyond a Politicized Conceptual Framework in Philosophy of Education, which will be published by the Theory and History of Education International Research Group. The interview can be accessed at https://www.youtube.com/watch?v=K_wvk_vHwVQ Nicholas Burbules is the Edward William and Jane Marr Gutgsell Professor in the Department of Educational Policy, Organization and Leadership at the University of Illinois, Urbana-Champaign. His primary research areas are philosophy of education, the ethics of communication, teaching through dialogue; and technology and education. Scott Johnston is Professor, jointly appointed to the Faculty of Education and Department of Philosophy at Memorial University, Newfoundland. His specializations are in philosophy of education, ethics, political philosophy, pragmatism, John Dewey, and Immanuel Kant.
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 | 0.077 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.039 |
| Scholarly communication | 0.009 | 0.026 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.007 | 0.019 |
| Insufficient payload (model declined to judge) | 0.007 | 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".