Warning—taboo words ahead! Avoiding attentional capture by spoken taboo distractors
Bibliographic record
Abstract
We examine whether the disruption of serial short-term memory (STM) by spoken taboo distractors is due to attentional diversion and unrelated to the underlying disruptive effect of sound on serial STM more generally, which we have argued is due to order cues arising from the automatic pre-categorical processing of acoustic changes in the sound conflicting with serial–order processing within the memory task (interference-by-process). We test whether the taboo-distractor effect is, unlike effects attributable to interference-by-process, amenable to top-down control. Experiment 1 replicated the taboo-distractor effect and showed that it is not merely a valence effect. However, promoting cognitive control by increasing focal task-load did not attenuate the effect. However, foreknowledge of the distractors did eliminate the taboo-distractor effect while having no effect on disruption by neutral words (Experiment 2). We conclude that the taboo-distractor effect results from a controllable attentional-diversion mechanism distinct from the effect of any acoustically-changing sound.
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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 | 0.000 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".