Bibliographic record
Abstract
One of the early key empirical findings of the happiness literature is that at higher levels of per capita real income there appears to be diminishing returns to income at least with regards to marginal changes in ‘happiness’ measured by various survey instruments. Although these results have been recently challenged, these earlier findings and the results of many contemporary studies suggest that an inelastic relationship exists between real per capita income and happiness after a relatively low threshold of per capita income is reached. Appling some of the results of prospect theory I argue that even if it were true that the marginal effect of income on happiness is zero, a reduction in income would probably reduce the level of happiness, yielding a kink in the ‘happiness curve’. Also, applying a target income approach to the happiness literature, one can argue that pursuing higher target income, in itself, is a means of increasing life satisfaction. These two theoretical instruments yield results consistent with some of the most recent empirical finding based on Gallup Poll Survey data. In addition, applying insights from the capabilities approach, I argue, that increasing income is a means of purchasing the capabilities to increase individual levels of happiness through the production of public goods, such as health care and education. A given marginal increase in income need not generate any increase in happiness if this income increase is highly unequally distributed in a population or is not used to purchase goods and services that contribute to increases in the level of happiness.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".