The economic well-being of nations is associated with positive daily situational experiences
Bibliographic record
Abstract
People in economically advantaged nations tend to evaluate their life as more positive overall and report greater well-being than people in less advantaged nations. But how does positivity manifest in the daily life experiences of individuals around the world? The present study asked 15,244 college students from 62 nations, in 42 languages, to describe a situation they experienced the previous day using the Riverside Situational Q-sort (RSQ). Using expert ratings, the overall positivity of each situation was calculated for both nations and individuals. The positivity of the average situation in each nation was strongly related to the economic development of the nation as measured by the Human Development Index (HDI). For individuals’ daily experiences, the economic status of their nation also predicted the positivity of their experience, even more than their family socioeconomic status. Further analyses revealed the specific characteristics of the average situations for higher HDI nations that make their experiences more positive. Higher HDI was associated with situational experiences involving humor, socializing with others, and the potential to express emotions and fantasies. Lower HDI was associated with an increase in the presence of threats, blame, and hostility, as well as situational experiences consisting of family, religion, and money. Despite the increase in a few negative situational characteristics in lower HDI countries, the overall average experience still ranged from neutral to slightly positive, rather than negative, suggesting that greater HDI may not necessarily increase positive experiences but rather decrease negative experiences. The results illustrate how national economic status influences the lives of individuals even within a single instance of daily life, with large and powerful consequences when accumulated across individuals within each nation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".