Innovating, gaining market share and fostering social inclusion: success stories in SME development
Bibliographic record
Abstract
This document represents a contribution made by the Tripartite Committee comprising the Organization of American States (OAS), the Inter-American Development Bank (IDB) and the Economic Commission for Latin America and the Caribbean (ECLAC) to the fourth Ministerial Meeting of the Pathways to Prosperity in the Americas Initiative, in Santo Domingo, on 5 October 2011. This initiative for promoting growth and prosperity provides a forum for countries to learn from each other's experience and for them to share lessons learned and best practices as they seek to put broader opportunities within the reach of everyone in the region. Fourteen Western Hemisphere countries are participating in the initiative: Canada, Colombia, Costa Rica, Chile, Dominican Republic, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Peru, the United States and Uruguay. OAS, IBD and ECLAC have supported this process since its launch in 2008. Against this backdrop, this document sets out lessons learned and success stories, both in the region and elsewhere, concerning the thematic areas identified as priorities for the initiative. These priorities include promoting the development of micro-, small, and medium-sized enterprises by supporting, among other things, their productive linkages and their access to credit and the global market; facilitating trade; training a modern labour force; and developing sustainable business practices. This document seeks to put these experiences at the service of the countries participating in Pathways to Prosperity in the Americas as they work to improve the living standards of their citizens. It is not an exhaustive recounting of success stories. Instead, it highlights those cases that stand out for their potential impact, their replicability in a variety of socio-economic and cultural contexts, their economic efficiency or their capacity to promote sustainable development.
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 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 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.340 | 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 teacher head, 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".