Toward an Integration of Goal Setting Theory and the Automaticity Model
Bibliographic record
Abstract
Two laboratory experiments were conducted to assess the extent to which goal setting theory explains the effects of goals that are primed in the subconscious on task performance. The first experiment examined the effect on performance of three primes that connote the difficulty levels of a goal in the subconscious. Participants ( n = 91) were randomly assigned to one of three conditions where they were primed with either a photograph of a person lifting 20 pounds (easy goal), 200 pounds (moderately difficult goal), or 400 pounds (difficult goal). Following a filler task, participants were asked to “press as hard as you can” on a digital weight scale. Participants who were primed with the difficult goal exerted more effort than those who were primed with the moderate or easy goal. The second experiment examined whether choice of goal difficulty level can be primed. Participants ( n = 133) were randomly assigned to one of two conditions. Those primed with a difficult goal consciously chose to set a more difficult goal on a brainstorming task than those who were primed with an easier goal. Similarly, their performance was significantly higher. Conscientiousness moderated the subconscious goal–performance relationship while the self‐set conscious goal partially mediated the subconscious goal–performance relationship.
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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 | 0.001 | 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) | 0.001 | 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".