Why Beautify the Plaza? Reproducing Community in Decentralized Neoliberal <scp>P</scp>eru
Bibliographic record
Abstract
Peruvian development and government analysts criticize communities for irrationally using local development funds deriving from recently instituted political decentralization to beautify their villages rather than to improve infrastructural services, education and health, or to alleviate poverty. This paper challenges this critique by explaining why such cosmetic improvements are of interest to rural people. Using a case study of the peasant community of Allpachico, I argue that these projects encourage the return of pensioners and visits from migrants. Residents and migrants are mutually dependent as a result of livelihood strategies based on agriculture and the foreign‐controlled resource extraction sector over the past 80 years. The relative position of these two groups in the social reproduction of the vernacular community has changed with the Peruvian political economy. Currently, in the neoliberal resource extraction economy, residents pragmatically opt to maintain relations with those who have stable wage or pension incomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".