Recovering Ancient and Medieval Contemplative Taxonomies as an Alternative to Bloom’s Taxonomy of Educational Objectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bloom’s taxonomy has become a pedagogical orthodoxy in schools. This paper challenges Bloom’s assumptions about thinking (the cognitive domain) and willing (the affective domain). A careful examination of ancient and medieval understandings – and of Thomas Aquinas’ contemplative taxonomy in particular – demonstrates how Bloom’s taxonomy is both disordered and reductionistic. The thesis of this paper is that, if education is to be truly aimed at our “highest happiness,” we must begin, in some small ways at least, to relate our educational efforts to the pursuit of wisdom. This pursuit, it is argued, involves engaging components of thinking and willing that transcend Bloom’s taxonomy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it