Spatial context and top-down strategies in visual search
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
Marvin M. Chun and Yuhong Jiang (1998) investigated the role of spatial context on visual search. They used two display conditions. In the Old Display condition, the spatial arrangement of items in the search display was kept constant throughout the experiment. In the New Display condition, the spatial arrangement of items was always novel from trial to trial. The results showed better performance with Old Displays than with New Displays. The authors proposed that repeated spatial context help guiding attention to the target location, thus they termed this effect Contextual Cueing. We present three attempts to reproduce this effect. Experiments 1 and 2 were near exact replications of experiments in Chun and Jiang's report, where we failed to obtain Contextual Cueing. Post-experimental interviews revealed that participants used different search strategies when performing the task: an 'active' strategy (an active effort to find the target), or a 'passive' strategy (intuitive search). In Experiment 3, we manipulated task instructions to bias participants into using active or passive strategies. A robust Contextual Cueing Effect was obtained only in the passive instruction condition.
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