Attention norms in Siegel’s <i>The Rationality of Perception</i>
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 Can we be responsible for our attention? Can attention be epistemically good or bad? Siegel tackles these under‐explored questions in “Selection Effects”, a pathbreaking chapter of The Rationality of Perception . In this chapter, Siegel develops one of the first philosophical accounts of attention norms . Her account is inferential: patterns of attention are often controlled by inferences and therefore subject to rational epistemic norms that govern any other form of inference. Although Siegel’s account is explanatorily powerful, it cannot capture a core attention norm in cognitive science: one should balance between exploratory and exploitative attention. For central cases of exploratory attention such as mind‐wandering, child‐like, and creative thinking are non‐inferential. Siegel’s view classifies them as “normative freebies” that are not subject to epistemic evaluation. We’re therefore left with a disjunctive conclusion: either Siegel’s inferentialist theory of attention norms is incomplete or cognitive scientists are wrong about the norms that govern attention.
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 | 0.000 |
| 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) | 0.000 | 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