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
1.5 Stay Alive is a nature film, music video-like documentary that emphasizes the consequences of a 1.5 degree increase in temperature that would negatively impact the Caribbean region (“1.5 Stay Alive: Science Meets Music in the Caribbean”). The film demonstrated the role that developed countries play in advancing and maintaining the climate crisis in the Caribbean. Disaster capitalism describes the exploitation by developed countries when responding to crises, intentionally creating a more unequal and undemocratic society. Using the example of Hurricane Maria, Klein states that Puerto Rico became broken because of deliberate, systematic interferences to power, water, health, communication, and food systems (2018). Alternatively, developed countries may supply the Caribbean with funds to produce and distribute locally grown produce. An example of what may be done with these funds can be seen in Cuba which created a self-sufficient urban agricultural economy. This would strengthen food security and increase the ability and knowledge to build back food systems following the effects of climate change (Quirk 2012). Information omitted includes details on how developed countries contributed to climate change vulnerabilities in the Caribbean. Environmental changes shape Caribbean agricultural trends which are already historically vulnerable owing to the by-products of colonial and plantation economies (Barker 2012, 42). The film advances the understanding of the effects of global warming in the Caribbean by not only showing the scientific perspective, but also the human side. Climate change affects more than just infrastructure, coral reefs, and economies, but it also affects people’s lives.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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