The Good Life of the Powerful
Bibliographic record
Abstract
A common cliché and system-justifying stereotype is that power leads to misery and self-alienation. Drawing on the power and authenticity literatures, however, we predicted the opposite relationship. Because power increases the correspondence between internal states and behavior, we hypothesized that power enhances subjective well-being (SWB) by leading people to feel more authentic. Across four surveys representing markedly different primary social roles (general, work, romantic-relationship, and friendship surveys; Study 1), and in an experiment (Study 2a), we found consistent evidence that experiencing power leads to greater SWB. Moreover, authenticity mediated this effect. Further establishing the causal importance of authenticity, a final experiment (Study 2b), in which authenticity was manipulated, demonstrated that greater authenticity directly increased SWB. Although striving for power lowers well-being, these results demonstrate the pervasive positive psychological effects of having power, and indicate the importance of spreading power to enhance collective well-being.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".