Bibliographic record
Abstract
This paper analyzes how democratization has affected the dynamics of candidate selection in South Korea. After democratization in the late 1980s, it was expected that intra-party democracy would follow. In response to increasing public demand, the major parties adopted primary systems in the early 2000s. Nonetheless, most candidates for the legislature are still nominated by a small number of central party elites without additional ballots in the local branches. To explain the persistence of such exclusive, centralized features of candidate selection, I highlight the limited impact democratization has had on the political environment in which the parties operate. More specifically, since the 1987 democratization process resulted in a compromise agreement established by a small number of party leaders, South Korea retained much of the political legacy from authoritarian times, such as an electoral system advantageous to the major parties and legal provisions restricting electoral campaigns, party activities, and political participation. The continuation of these political institutions makes radical candidate selection reform highly unlikely as the party elites have no incentive to expand and decentralize the selection process. Without significant changes to the political institutions at the national level, the dominance of the central party elite over the final outcome of candidate selection looks likely to continue for the foreseeable future.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".