Preliminary evidence for a selective agency-boosting effect of psychosocial stress
Bibliographic record
Abstract
• Across 2 studies, explicit and implicit methods are used to explore stress and SoA. • Under stress, temporal binding selectively increases after 700 ms delays. • No statistically significant relationship was found between stress and explicit SoA. • Increased action-effect intervals produce a potential “stress-enabled agency boost” Sense of Agency (SoA) arises from the perception of being in control of one’s own actions and their outcomes. Many contextual and individual difference variables have been found to influence the SoA. Here, we focused on elucidating the potential relationship between psychosocial stress and the SoA across two studies. Psychosocial stress was induced via the Trier Social Stress Test (TSST) and agency was assessed in a task involving production of a voluntary action that resulted in an auditory effect 100 ms, 400 ms or 700 ms later. In Study 1, we used an explicit self-reported measure of agency in the form of a perception of control rating, and in Study 2 we used an implicit measure of agency in the form of temporal estimates of the interval between an action and an effect, so called intentional binding (IB). The results of Study 1 (explicit) showed that undergoing the TSST relative to a control condition increased SoA for outcomes that occur after a 700 ms delay. However, this effect was weak and did not survive correction for multiple comparisons. In Study 2 (IB), temporal estimates in the stress condition were significantly shorter than those in the control condition, exclusively for action-effect time delays of 700 ms. We conclude that this increased IB for 700 ms delays after induction of psychosocial stress reflects a potential “stress-enabled agency boost”, and that such an agency boost might be associated with the fight-or-flight stress response. Directions for future research are suggested.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".