Creating a Social Wasteland? Non-Traditional Agricultural Exports and Rural Poverty in Ecuador
Bibliographic record
Abstract
Neoliberal economic policies in Latin America have resulted in the rapid growth of nontraditional agricultural exports (NTAE). This growth is often seen as contributing to the alleviation of rural poverty. The paper examines this view with the focus on Ecuador, using the World Bank’s definition poverty as a reference. It is argued that the flower export expansion has created employment opportunities but did not allow the rural poor to raise themselves above the poverty line. Moreover, flower employment has undermined the pre-existing social networks and community organizations, increasing the levels of insecurity among rural families and undermining their ability to influence the processes of decision making. Resumen: Creando un páramo social? Exportaciones agrícolas no-tradicionales y pobreza rural en EcuadorLas políticas económicas neo-liberales en América Latina han resultado en el rápido crecimiento de las exportaciones agrícolas no tradicionales (EANT), lo que es considerado a menudo como un alivio de la pobreza rural. En este artículo se estudia esta visión para el caso de Ecuador, utilizando como referencia la definición de pobreza del Banco Mundial. Aunque se dice que la expansión en la exportación de flores ha creado oportunidades de empleo, no ha logrado que los pobres rurales crucen la línea de la pobreza. Además, el empleo en este sector ha socavado las redes sociales y organizaciones comunitarias anteriores, elevando los niveles de inseguridad entre las familias rurales y minando su capacidad de intervención en el proceso de toma de decisiones.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".