The impact of better‐ Versus worse‐than‐average comparisons on beliefs about how life satisfaction is unfolding over time, affect, and motivation
Bibliographic record
Abstract
Abstract We investigated comparisons to the average other in shaping how individuals view their lives as unfolding over time, affective reactions, and motivation. Participants described their current life (Study 1; N = 382; M age = 30.01 years; 43% female) or their life as unfolding over time (Study 2; N = 451; M age = 30.89; 54% female) as either better (BTA) or worse (WTA) than the average person their age and gender (both studies included a “no comparison” control group). In both studies the BTA (vs. WTA) condition resulted in greater perceived improvement in life satisfaction, more positive affective reactions, and greater motivation to achieve one's goals for the future. Thus, we conclude that viewing one's current life or one's progress in life over time as better (vs. worse) than average leads to more favourable temporal life evaluations, more positive affective responses, and greater motivation.
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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 | 0.001 |
| 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".