New Developments in and Directions for Goal-Setting Research
Bibliographic record
Abstract
Abstract. Goal setting is an “open” theory built on inductive findings from empirical research. The present paper briefly summarizes this theory. Emphasis is then given to findings that have been obtained in the present millennium with regard to (1) the high performance cycle, (2) the role of goals as mediators of personality effects on performance, (3) personality variables as moderators of goal effects on performance, the effect of (4) distal, (5) proximal, and (6) learning goals on performance on tasks that are complex for people, (7) the ways in which priming affects the impact of a goal, (8) the interrelationship between goal setting and affect, and (9) the results of goal setting by teams. Potential directions for research on goal setting in the workplace are suggested with regard to goal abandonment, perfectionism, an employee's age, subconscious goals, and the relationship between goals and knowledge.
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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 | 0.049 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.014 | 0.030 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".