Patrones de consumo energético en productores de quinua del altiplano Sur de Bolivia
Bibliographic record
Abstract
This paper analyzes the energy consumption of quinoa producers in the Bolivian altiplano. The objective of the research is to evaluate how energy consumption influences the total expenditure of producers and, in addition, to provide recommendations to promote sustainable energy practices. Previous studies in similar contexts indicate that access to modern energy sources is related to higher value added in agricultural production. The present research includes a survey of 137 quinoa producers in four communities in the altiplano. It measures biomass consumption, the use of renewable technologies and the impact on agricultural production. Econometric models (i.e. Ordinary Least Squares (OLS) and quantile regressions) were applied to analyze the relationship between expenditure on different energy sources and total expenditure. The findings reveal that spending on electricity has a positive relationship with total spending, suggesting that higher incomes allow access to more efficient sources. In contrast, spending on firewood and fuel has negative relationships, indicating that there is a dependence on traditional sources linked to energy poverty. Energy deprivation significantly affects lower-income households and evidences their vulnerability. In addition, the use of technology is associated with greater energy efficiency, and highlights the need for policies that promote access to modern technologies.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".