Posner’s Endogenous Beam Is (Still) Not Treisman’s Glue
Bibliographic record
Abstract
Abstract: Posner’s beam and Treisman’s glue are metaphors of visual attention that stimulated research programs on exogenous and endogenous modes of attentional control and feature integration theory. Briand and Klein (1987) asked, “Is Posner’s beam the same as Treisman’s glue,” positing that the orienting of Posner’s spatially confined beam (spotlight of attention) could be the mobilization of the same attentional machinery described by Treisman as performing object feature integration. Based on the patterns of interaction between cue condition and the opportunities for illusory conjunctions, they concluded the answer depended upon the mode of control: An interaction suggested a yes answer for exogenous control while additivity suggested no for endogenous control, a difference in the effects of attention suggesting that there may be two independent beams. Kawahara and Miyatani (2001) challenged the lack of interaction between endogenous cues and task type (feature targets vs. conjunction targets) using a different paradigm that emphasized search and contained more items. After noting the importance of presenting all the displayed items at an attended or unattended location, we report two experiments that replicate Briand with two-item arrays and extend this finding to four-item arrays, strongly supporting the claim that Posner’s endogenous beam is not Treisman’s glue.
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.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".