Happiness in the tropics: climate variables and subjective wellbeing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Changes in climatic patterns are expected to have significant effects on health and wellbeing. However, the literature on the effect of climate on subjective wellbeing remains scant and existing studies focus mostly on developed countries or cross-country analyses. This paper aims to identify the relationship between climate conditions on happiness after controlling for individual and social characteristics. Ecuador, a geographically fragmented country with varying climate conditions across municipalities, constitutes an ideal case study to assess the effect of climate variables on happiness. We employ a cross-section analysis to identify the effect of temperature, precipitation and humidity on happiness. The paper shows that climate conditions constitute an important determinant of people's subjective wellbeing. The results also suggest that income and education attenuate the effect of temperature on happiness and that substantial differences are observed depending on whether places are hot/humid or cold/dry.
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.
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 | 0.000 |
| 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 it