The Influence of External Stimuli on the Generation of Voluntary Thoughts
Bibliographic record
Abstract
A central question in psychology has been how involuntary cognitive processes interact with their voluntary counterparts. Stemming from the flanker and Stroop tasks, which have revealed that involuntary cognitive processes can counter and interfere with voluntary cognitive processes, the reflexive imagery task (RIT) has shown that stimuli can elicit involuntary higher-order cognitions. The extent to which stimulus-elicited involuntary processes can influence voluntary processes remains unknown. In our study, participants were instructed to, when presented with a cue (a square frame), think of a random word and disregard a line drawing that was presented concurrently. Would the presence of the line drawing influence the generation of the verbal imagery? Despite the participant’s intentions, the to-be-ignored line drawing had an influence over the participant’s response at a reliable, substantive rate: On over 35% of the trials, the word the participant thought of was associated with the name of the line drawing. On half of the trials, no line drawing was presented (the “No Line Drawing” condition). Participants’ sense of control and the extent to which the response (i.e., the word) was due to “the self,” was stronger in the No Line Drawing condition than in the condition in which a line drawing was presented. The theoretical implications of these findings are discussed.
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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 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".