United by Discord, Divided by Consensus: National and Sub-national Articulation in Bolivia and Peru, 2000–2010
Bibliographic record
Abstract
From 2000 to 2010, Bolivia and Peru underwent similar processes of political decentralization toward the meso level of the government. Three elections later in Peru and two in Bolivia, the ability of national political parties to articulate interests differs markedly between the two countries. Peru tends toward fragmentation with national parties incapable of participating or successfully competing in subnational elections, while in Bolivia, the Movimiento al Socialismo (MAS) – and other parties to a lesser extent – are increasingly capable of participating and winning subnational offices. This paper argues that, despite having undergone very similar institutional reforms, the difference between the cases can largely be explained by two “society-side” variables: the caliber of the political ideas in debate and political social density. The substantive quality of ideas in debate and a greater political social density have been crucial to the Bolivian trend, while their absence has lessened the possibility of anything similar occurring in Peru. In general terms, the article sheds light on the social conditions that favor party-building in a context of decentralization reform.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".