Bibliographic record
Abstract
This commentary is a review of the findings and ideas reported in the preceding nine articles on the effects of distraction on aspects of cognitive performance. The articles themselves deal with the disruptive effects of distraction on recall of words, objects and events, also on visual processing, category formation and other cognitive tasks. The commentary assesses the part played by "domain-general" suppression of distracting information and the "domain-specific" competition arising when tasks and distraction involve very similar material. Some forms of distraction are meaningfully relevant to the ongoing task, and Treisman's (1964) model of selective attention is invoked to provide an account of findings in this area. Finally, individual differences to vulnerability to distraction are discussed; older adults are particularly affected by distracting stimuli although the failure to repress distraction can sometimes prove beneficial to later cognitive performance.
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.036 | 0.037 |
| Insufficient payload (model declined to judge) | 0.003 | 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".