People in historically rice-farming areas are less happy and socially compare more than people in wheat-farming areas.
Bibliographic record
Abstract
Using two nationally representative surveys, we find that people in China's historically rice-farming areas are less happy than people in wheat areas. This is a puzzle because the rice area is more interdependent, and relationships are an important predictor of happiness. We explore how the interdependence of historical rice farming may have paradoxically undermined happiness by creating more social comparison than wheat farming. We build a framework in which rice farming leads to social comparison, which makes people unhappy (especially people who are worse off). If people in rice areas socially compare more, then people's happiness in rice areas should be more closely related to markers of social status like income. In two studies, national survey data show that income, self-reported social status, and occupational status predict people's happiness twice as strongly in rice areas than wheat areas. In Study 3, we use a unique natural experiment comparing two nearby state farms that effectively randomly assigned people to farm rice or wheat. The rice farmers socially compare more, and farmers who socially compare more are less happy. If interdependence breeds social comparison and erodes happiness, it could help explain the paradox of why the interdependent cultures of East Asia are less happy than similarly wealthy cultures. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".