Sustainability science and education in Haiti and Puerto Rico
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
This paper reports on the results of a workshop in Haiti and Puerto Rico to capture what priorities may be important to build sustainability sciences and education. In 2015, approximately 35 individuals attended all or part of the workshop at each location. Participants included academic leaders, university faculty, secondary school teachers, representatives of non-profit organizations, and university and high school students. Haitian participants called attention to the need for reforestation training, systemic solutions for waste management, and sustainable marine resources management. In Puerto Rico, participants called for more training to link civic engagement with sustainable development, social determinants of health, and programming on tsunami preparation and recovery. Members of both workshops asked for sustainability science and education advances in renewable and alternative energy development, general disaster and climate change impact preparedness (e.g. drought), and sustainable agriculture. Haitian and Puerto Rican participants also shared the view that engaging sustainability requires higher educational institutions to partner with communities, primary and secondary school teachers, policy-makers, and especially young persons, to reinforce the values of sustainability, and collectively work across sectors to learn through trial and error together.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it