Positive affect increases the breadth of attentional selection
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
The present study examined the thesis that positive affect may serve to broaden the scope of attentional filters, reducing their selectivity. The effect of positive mood states was measured in two different cognitive domains: semantic search (remote associates task) and visual selective attention (Eriksen flanker task). In the conceptual domain, positive affect enhanced access to remote associates, suggesting an increase in the scope of semantic access. In the visuospatial domain, positive affect impaired visual selective attention by increasing processing of spatially adjacent flanking distractors, suggesting an increase in the scope of visuospatial attention. During positive states, individual differences in enhanced semantic access were correlated with the degree of impaired visual selective attention. These findings demonstrate that positive states, by loosening the reins on inhibitory control, result in a fundamental change in the breadth of attentional allocation to both external visual and internal conceptual space.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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