Everyday Expertise: Land Regularization and the Conditions for Land Grabs in Petén, Guatemala
Why this work is in the frame
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Bibliographic record
Abstract
Advocates claim that market-assisted land reform (MALR) promotes economic development and reduces poverty by improving the security of private property rights and the efficiency of land markets. However, scholars argue that MALR often benefits elites at the expense of the disadvantaged and forces intended beneficiaries to resist or make difficult compromises. Nevertheless, this critical literature largely glosses everyday processes of implementation that help this policy get traction in particular locations. This paper examines the work of regularizing (titling) land in the context of a World-Bank-funded MALR project in northern Guatemala. Specifically, the focus is on the meaning-making work of field technicians who seek to convince campesinos (peasants) to participate in this regularization project. In their recruiting efforts, these technicians creatively link neoliberal slogans, human rights narratives, and exclusionary visions of nation, race, and property. By examining how technicians elaborate knowledge in the field and on the fly, this study reveals spheres of politics where regularization could be modestly contested or transformed. Such politics are worth attending to because in northern Guatemala and elsewhere, regularization contributes to conditions for land grabs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it