Enfrentar as mudanças climàticas na agropecuària brasileira : o plano ABC como territorialização de uma inovação conservadora
Bibliographic record
Abstract
With the international consolidation of the global warming thesis, the issue of climate change has been making its presence felt in the debate arenas, causing successive governments to indicate changes in their climate-critical stances with a view to controlling greenhouse gas emissions. In view of this, in the 2000s Brazil took important steps in its national climate governance by creating, among other instruments, the Sectoral Plan for Mitigation and Adaptation to Climate Change for the Consolidation of a Low Carbon Economy in Agriculture (ABC Plan), the main Brazilian public policy to directly relate the climate issue to agriculture, currently called ABC+. However, although announced by the state and the mainstream media as a unique and innovative policy, some aspects of its conception and practical operation lead us to establish as the objective of the thesis to analyze, from the perspective of innovation, the coherence and consistency of the work carried out by the Brazilian state in tackling climate change through agriculture. To do this, we used the theoretical approach of the Geography of Innovation and the analytical category of the Agricultural Innovation System, linking the sphere of innovation to the domain of territory. The methodological procedures included a theoretical review of the central theme of the research, documentary research to gather primary and secondary data and field research in the previously delimited study area. At this stage, semi-structured interviews were conducted and visits were made to rural properties with different socio-economic and environmental realities. As the main result of the thesis, we highlight the fact that the ABC Plan, through its conception and practice, has been promoting the territorialization of a conservative innovation in the countryside, indicating that the current system of agricultural innovation is not far removed from a historical selective and unequal pattern of promoting development among the Brazilian agricultural sector.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".