Happiness Maximization Is a WEIRD Way of Living
Bibliographic record
Abstract
Psychological science tends to treat subjective well-being and happiness synonymously. We start from the assumption that subjective well-being is more than being happy to ask the fundamental question: What is the ideal level of happiness? From a cross-cultural perspective, we propose that the idealization of attaining maximum levels of happiness may be especially characteristic of Western, educated, industrial, rich, and democratic (WEIRD) societies but less so for others. Searching for an explanation for why "happiness maximization" might have emerged in these societies, we turn to studies linking cultures to their eco-environmental habitat. We discuss the premise that WEIRD cultures emerged in an exceptionally benign ecological habitat (i.e., faced relatively light existential pressures compared with other regions). We review the influence of the Gulf Stream on the Northwestern European climate as a source of these comparatively benign geographical conditions. We propose that the ecological conditions in which WEIRD societies emerged afforded them a basis to endorse happiness as a value and to idealize attaining its maximum level. To provide a nomological network for happiness maximization, we also studied some of its potential side effects, namely alcohol and drug consumption and abuse and the prevalence of mania. To evaluate our hypothesis, we reanalyze data from two large-scale studies on ideal levels of personal life satisfaction-the most common operationalization of happiness in psychology-involving respondents from 61 countries. We conclude that societies whose members seek to maximize happiness tend to be characterized as WEIRD, and generalizing this across societies can prove problematic if adopted at the ideological and policy level.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".