Divergent effects of distance versus velocity disturbances on emotional experiences during goal pursuit.
Bibliographic record
Abstract
Disturbances are factors outside of a person's control that influence goal progress. Although disturbances are typically included in theoretical accounts of goal pursuit, relatively little empirical research has explicitly considered the effects of disturbances on the goal-striving process. We address this gap in the literature by examining the effects that disturbances have on the emotional experience of goal pursuit. More importantly, we differentiate between distance disturbances (changes to the amount of progress made) and velocity disturbances (changes to the rate of progress made). We conducted 2 experiments (N = 62 and N = 134) in which participants completed work simulation tasks to earn a $5.00 reward. Partway through the experiment participants' progress was inhibited by either a distance disturbance or a velocity disturbance. Importantly, the distance and velocity disturbances were equated in terms of their influence on the likelihood of obtaining the cash prize. In both studies the introduction of a disturbance decreased enthusiasm and increased frustration. However, over time the effects of distance and velocity disturbances on enthusiasm and frustration diverged. Specifically, the velocity disturbance had a more enduring effect on these emotions, relative to the distance disturbance. Downstream, in Study 1 enthusiasm positively predicted goal commitment. In Study 2 enthusiasm positively predicted goal commitment, effort, and task performance. Likewise, in Study 2 frustration negatively predicted goal commitment and task performance. Therefore, relative to distance disturbances, velocity disturbances appear to be more disruptive to goal pursuit. We discuss theoretical implications and practical implications for managing employee motivation. (PsycINFO Database Record
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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 | 0.006 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".