Teaching and Learning: Epistemic, Metaphysical and Ethical Dimensions—Introduction
Bibliographic record
Abstract
This Introduction to the Special Issue, Teaching and Learning: Epistemic, Metaphysical and Ethical Dimensions, ponders the truism that education is of fundamental importance in human life—and its relation to philosophy. No credible natural-historic description of what a human being is could fail to give education a central place. Yet the concept of education has often been neglected by philosophers, especially those working in the Anglo-American mainstream. It seems, however, that the prejudices at the root of this neglect are on the wane, and more and more philosophers are beginning to recognise that education is of profound philosophical significance, entering into questions of the nature of knowledge, theoretical and practical reason, the formation of mind and its relation to the world, and the cultivation of moral vision. The time is ripe then for a renewed dialogue between philosophers of education and those in the ‘mainstream’ who have come to perceive the philosophical significance of education. The papers in this Special Issue aim to foster such a dialogue. To place them in context, this Introduction considers: the prospects for a robust epistemology of pedagogy that will escape the familiar frustrations of traditional epistemology; the relevance of the epistemology of testimony for illuminating teaching and learning; the teacher as the voice of the discipline; the cultivation of practical and moral knowledge, skills and habits; the scope and limits of new learning technologies; and the place of education in characterising the human life-form. The moral is that it is hard to see how we can do epistemology, metaphysics and ethics—this is to say, do philosophy—without having education in view.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 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".