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
Fiction might be dismissed as observations that lack reliability and validity, but this would be a misunderstanding. Works of fiction are simulations that run on minds. They were the first kinds of simulation. All art has a metaphorical quality: a painting can be both pigments on canvas and a person. In literary art, this quality extends to readers who can be both themselves and, by empathetic processes within a simulation, also literary characters. On the basis of this hypothesis, it was found that the more fiction people read the better were their skills of empathy and theory-of-mind; the inference from several studies is that reading fiction improves social skills. In functional magnetic resonance imaging meta-analyses, brain areas concerned with understanding narrative stories were found to overlap with those concerned with theory-of-mind. In an orthogonal effect, reading artistic literature was found to enable people to change their personality by small increments, not by a writer's persuasion, but in their own way. This effect was due to artistic merit of a text, irrespective of whether it was fiction or non-fiction. An empirically based conception of literary art might be carefully constructed verbal material that enables self-directed personal change. WIREs Cogn Sci 2012, 3:425-430. doi: 10.1002/wcs.1185 For further resources related to this article, please visit the WIREs website.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it