Bibliographic record
Abstract
This study explores the origins of pervasive elderly poverty in South Korea, which persists despite the continuous expansion of welfare programs and the consolidation of popular democracy in the country. Predicated upon the historical-institutional details of the development of welfare programs, this article examines and elucidates how the instrumentalization of welfare policy-making since the onset of state-led industrialization and the progress of electoral democracy since the democratic transition have hindered the implementation of e ective anti-poverty policies. It argues that the exponential politicization of welfare issues amid the demise of the agenda-setting and implementation capacity of the welfare bureaucracy has resulted in a political preference for low-benefit, quasi-universal solutions without an increase in taxes or contributions, which has crowded out the policy option of imposing su ciently generous measures targeted at this vulnerable segment of society. As pervasive elderly poverty persists, old-age welfare has been substantially privatized and dualized, compelling seniors to find market-based alternatives or to work in low-paying precarious labour sectors. Consequently, trust in South Korea's public welfare system has declined, impeding the formation of pro-welfare solidarity despite the overall growth of the universalist welfare system and popular democracy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".