Estrangeirização de terras nos EUA e a cooperação transnacional dos movimentos sociais: a atuação da USFSA
Bibliographic record
Abstract
The phenomenon of land grabbing has attracted international attention due to the contradictions and social reactions that involve the progress of this process. The phenomenon generally affects traditional communities in poor or developing countries, however, it has been identified that it is also affecting traditional communities in developed countries such as the USA, Canada, Australia. Thus, this dissertation seeks to analyze the foreignization of land in the USA, that is, the USA as a target for land investments. Starting from the contradictions that involve the acquisition of land by foreigners, the research has the central objective of understanding why social movements cooperate against the foreignization of land based on the actions of the US Food Sovereignty Alliance. In this way, specific objectives were defined to analyze the land foreignization in the USA, to study the literature on the transnational cooperation of global civil society and to analyze the social reactions to the land foreignization in the USA. To achieve the proposed objectives, in the methodological scope, a qualitative research was developed, using the deductive method of analysis. The analysis techniques used were bibliographic review, document analysis, in addition to field research for conducting semi-structured interviews, which also took place in a virtual manner. After constructing the panorama of land alienation in the USA, identifying the scale of the phenomenon, the main actors, areas of investment and socioeconomic consequences, we sought to present the approaches of transnational rural movements, globalization from below and Transnational Advocacy Networks (TAN) as main approaches to understand the relationship between the Independent Variable (VI) and the Dependent Variable (DV). Based on the analysis of the USFSA's performance, we identified that social movements cooperate against the foreignization of land due to the need to respond globally to international private actors who tend to limit access to land by traditional communities. Cooperation, which takes place transnationally, can be considered as the main action strategy of these movements that seek support, solidarity and sharing information and experiences at the international level, without neglecting the valorization of grassroots communities.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| 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".