Hope and Its Distribution in Rural Tanzania
Why this work is in the frame
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Bibliographic record
Abstract
Recent research at the intersection of psychology and economics sheds light on the influence of hope on economic decisions. A body of that work concentrates on the economics of hope in developing country contexts. We identify two notable gaps: lack of attention to the measurement of hope as a latent psychological construct, and consequently, the lack of description and characterization of hope as a variable that can be measured and targeted. This study addresses these gaps by assessing the effectiveness of a novel hope measurement instrument, utilizing a large primary dataset collected in rural Tanzania. We estimate hope distributions across over 5,000 individuals and conditionally within subgroups defined by gender, region, recent shock, age, food security, income source, and religiosity. A positively-worded question about faith had the greatest information content among all questions, negatively worded questions were more effective in distinguishing people with relatively high hope. Employing generalized structural equation models, we observe significant variations in hope across sub-groups. Correcting for measurement distortions, we find significant heterogeneity in hope distributions across individuals and subgroups. The presence of an income-earning household member and religiosity yield the most pronounced shifts in hope distributions.
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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) | 0.000 | 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