Democratic Deliberation and the Resource Curse
Bibliographic record
Abstract
Abstract Oil and gas discoveries in developing countries are often associated with shortsighted economic policies and, in response, with calls to insulate resource management from populist impulses. The authors report on a randomized experiment that tested methods to overcome this apparent tension between sound resource governance and democratic politics. Soon after Tanzania's discovery of major natural gas reserves, the authors invited a nationally representative sample of voters to take part in an intensive public deliberation of policy options, at an event featuring nationally recognized experts and small-group discussions. Democratic deliberation reinforced the public's strong preference for rapid spending of gas revenues, but also increased support for various prudential and economically orthodox measures, such as the independent oversight of gas revenues, limits on government borrowing, and selling gas abroad rather than subsidizing fuel at home. These effects were driven by deliberation per se, rather than a pure information treatment, and show no evidence of contamination by facilitator effects or peer effects in group deliberations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.140 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".