Neo-liberalism, Semi-clientelism and the Politics of Scale in Mexican Anti-poverty Policies
Bibliographic record
Abstract
Abstract This article examines the implications of the multi-scalar politics of Mexican anti-poverty policy for the long-term process of democratization. The federal anti-poverty policy, Progresa/Oportunidades, was designed to eliminate traditional clientelistic practices. While more obvious practices of pork-barrel politics have been eliminated in poverty alleviation programs, continued practices of top-down processes of program design and implementation strategies have resulted in the emergence of semi-clientelism. Argued in this paper is that municipal and state political actors have responded to these federal policies in ways that may or may not promote deeper levels of democracy, and which have led to the reconstitution of semi-clientelism. The paper draws upon recent revisionist approaches to political clientelism, and introduces a multi-scalar approach borrowed from political geography. Based on this theoretical approach, the article examines the role of state and municipal authorities in the delivery of federal anti-poverty benefits within the Oportunidades conditional cash transfer program.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".