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
Conceptual fragmentation is when a term assumed to have one meaning is found to have many. When these different definitions overlap in meaning and application confusion and wasted effort follows. "Attention" is such a fragmented term. The response to conceptual fragmentation is simple. Stop using the original term. Our reticence to do so reflects false beliefs about attention. "Attention" is not an old term, but a modern one. Its original meaning is not related to our contemporary intuitions. Attention is not a necessary concept; psychology made substantial progress, even in cognitive areas, during the years when its use was banished. Attention is just one among many examples of conceptual fragmentation in psychology. The root cause is a dearth of theory driving cognitive experimentation. Theoretical clarity is enhanced when fundamental concepts can be expressed in a mathematical form. When theories are stated in mathematical language it opens the door to rigorous cross-domain comparisons using tools like category theory. This article is categorized under: Psychology > Attention Neuroscience > Cognition.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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