Bibliographic record
Abstract
If educators presuppose that brain and mind are synonymous, perhaps it is out of necessity. Such an equivalency might be required in order for mind to be accessible, knowable and a ‘thing’ like the brain is. Such a presupposition, that mind is a thing which we can understand nonetheless rests on an insecure foundation. As suggested by philosopher John Searle in the opening quotation, this might explain the historical and present day interest in metaphors of mind, where comparisons to unlike things are used to help philosophers, psychologists, and educators more securely understand how mind really ‘works.’ Educators have an enormous investment in explicating how mind works, as they are required to observe and measure what is going on in the minds of students. In practice, mind has to be a thing for how does one reasonably talk about accomplishing such requirements if mind is merely some philosophical abstraction? This article will explore two metaphors of mind suggesting that embedded within each are presuppositions of epistemological and pedagogical significance.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.007 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".