Curbing the Resource Curse:Mongolian Democracy’s Associational Ally
Bibliographic record
Abstract
Mongolia has had an unbroken record of democratic rule for a quarter of acentury, but natural resources loom to curse its promising political pathway.Natural resources have cursed more than a handful of fledgling democraciesin the post-Cold War era, but not Mongolia. Despite neighboring China andRussia’s unquenchable thirst for exploitable resources, democracy remains theonly game in town in Mongolia. Abundant scholarship on the resource cursesays surprisingly little about factors that condition low-income democracies’drowning in resource affluence. This essay argues that Mongolia sustainsdemocracy thanks to at least one political-institutional factor: a vigorouscivil society that perseveringly checks and monitors state power, pushes backagainst powerful economic interests, articulates and presses social demandsof underprivileged groups in society, and, not least, aids the state. Theanalysis shows the variety of weapons that civil society uses to champion anopen polity, keep citizens on notice, and tie the hands of powerful economicinterests. Skillfully applying these means, civil society has been key to makingMongolia punch above its weight politically, economically, and in terms ofsocial welfare provision for a quarter of a century.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".