Can the Differences Between Education and Neuroscience be Overcome by Mind, Brain, and Education?
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
ABSTRACT— The new field of Mind, Brain, and Education (MBE)—sometimes called educational neuroscience—is posited as a mediator between neuroscience and education. Several foundational concerns, however, can be raised about this emerging field. The differences between neuroscience and education are many, including differences in their histories, philosophies, and epistemologies. Historically, science and education have demonstrated separate, but interwoven, influences on society; philosophically, the values by which they operate are often in opposition; and epistemologically, the fields have relied on different conceptualizations of knowledge. Discussion about these differences has been largely absent in attempts to promote MBE. Two steps are proposed to respond to this omission. First, encouraging discussion about disciplinary differences and assumptions may enable better understanding between disciplines and facilitate the establishment of a more collaborative research community. Second, a transdisciplinary framework that focuses on salient issues of interest across disciplines should be considered. Transdisciplinarity aims for the creation of an inclusive research environment that transcends traditional disciplinary approaches to complex problems. This article initiates an exploration of disciplinary differences and proposes commitment to transdisciplinarity as a guiding principle that may increase the viability of MBE as a mediating field between neuroscience and education.
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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