Interview with the Assistant Secretary General of the Organization of American States OAS Ambassador Nestor Mendez ‘Forward Looking Vision of the OAS’
Bibliographic record
Abstract
Nestor Mendez was elected to be the ninth Assistant Secretary General of the Organization of American States (OAS) on March 18, 2015. He began serving his five-year term on July 13, 2015 with a commitment to work closely with the Secretary General and the member states to reinvigorate and modernize the institution. The Assistant Secretary General based his platform on five main thematic areas: improving regional inter-connectivity; fostering economic growth, addressing the impacts of climate change and natural disasters; promoting partnerships for development, and working to empower and respond to the needs of the youth across the hemisphere. Upon receiving the mandate from member states, he pledged his “unwavering commitment to seize the opportunity that is before us to work together to transform the OAS into the Organization that we want and that the people of the Americas deserve.” Prior to his election, Nestor Mendez was a career diplomat in the Foreign Service of Belize. He served as the Ambassador to the United States of America, Permanent Representative to the OAS, and NonResident High Commissioner to Canada. He holds a Master’s Degree in International Policy and Practice from George Washington University in Washington, D.C., a Graduate Level Certificate in Diplomatic Studies from Oxford University in Oxford, United Kingdom, and a Bachelor’s Degree in Business Administration from the University College of Belize in Belize City, Belize.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".