Tomada de crédito e busca por proteção da produção na cafeicultura brasileira.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to the importance of rural credit in stimulating investments, funding and marketing in coffee production, and the strategic relevance of rural insurance to investment protection and business competitiveness, this study analyzes the percentages of use of credit and insurance, in relation to the levels of management of companies, size and adoption of agricultural certification, aiming to support the decisionmaking of institutions linked to the provision of services or establishment of incentive programs and access to credit and rural insurance. Information on 1,136 production units in the main Brazilian coffee regions was used. We used the Management Degree Identification Method - MIGG-Café. It was observed that the adoption of credit above 70.0% and rural insurance close to 50.0%. Their joint use is positively correlated to establishments with higher levels of management. It was concluded that there is ample opportunity for evolution in business credit management and risk management in coffee.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 0.005 |
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