Behavioral and Experiential Self-Regulations in Psychological Well-Being under Proximal and Distal Goal Conditions
Bibliographic record
Abstract
This study examined the relationship of goal-related components of cybernetic, behavioral, and experiential self-regulations to psychological well-being under two types of conditions, the pursuit of intrinsic goals in general and specific intrinsic goals for the academic term. In an online survey, undergraduates (N = 186) completed global measures of psychological well-being, behavioral and experiential self-regulations, and rated themselves on goal-related self-regulatory components. Correlations indicated that most of the cybernetic, behavioral and experiential self-regulatory variables were associated with each other and with well-being. In terms of the goal-related self-regulatory components, when pursuing intrinsic goals more generally, the experiential self-regulatory component of enjoyment of the activity predicted well-being. However, when pursuing intrinsic term goals, the cybernetic self-regulatory component of perceived goal progress and the behavioral self-regulatory component of self-reinforcement for goal progress predicted well-being. The findings extend theoretical conceptualizations of psychological well-being by integrating compatibilities between cybernetic, behavioral, experiential self-regulatory processes and motivational conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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 teacher head, 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".