Performance on Multiple Different Global/Local Processing Measures Predict Individual Differences in the Attentional Blink
Bibliographic record
Abstract
When the second of two targets (T2) is presented temporally close (within 500ms) to the first target (T1), accuracy for identifying/detecting T2 is markedly diminished -- an attentional blink (AB). Using Navon letter stimuli, Dale and Arnell (2010) demonstrated that individual differences in dispositional attentional focus (i.e. global or local) were associated with performance on the AB task, such that individuals who focused more on the local level information were more susceptible to the AB. The purpose of the current study was to extend this finding by using three different measures of global/local processing to predict AB performance. In the first global/local task, participants viewed congruent or incongruent Navon letters, and were asked to attend to the local or global level so that global and local interference could be estimated. For the second task, participants viewed incongruent hierarchical shapes (e.g., a square made of triangles), and then made a forced-choice decision about which of two shapes best matched the hierarchical shape. For the third task, participants viewed superimposed faces containing the high spatial frequency information of one individual and the low spatial frequency of another individual. They then indicated which of two intact faces had been presented as the hybrid. Participants also completed a standard AB task. As hypothesized, performance on all three global/local tasks predicted subsequent AB performance, such that individuals with a greater preference for the global (low spatial frequency) information showed a reduced AB. However, a regression analysis revealed that while performance on all three global/local tasks predicted the AB, they all predicted unique variance in AB magnitude. This suggests that if indeed these global/local tasks are measuring some aspect of global/local processing, they are all measuring unique, rather than similar, processes. Meeting abstract presented at VSS 2012
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".