Shifting to Circular Manufacturing in the Global South: Challenges and Pathways
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
As the Global South shifts towards increased manufacturing, the negative effects on climate change and environmental pollution raise serious concerns. These global effects are increasingly felt locally, as reflected in health surveys throughout the Global South. The world cannot afford to wait for a natural development process to take place in which rising incomes might curb pollution. This article examines the challenges of reforming manufacturing in the Global South towards more sustainable practices. It also focuses on the lessons of the Sustainable Manufacturing and Environmental Pollution Program (SMEP) which has funded a series of environmental improvement projects across sub-Saharan Africa and South Asia aimed at reducing pollution in the manufacturing process. The lessons learned from these projects include the need to improve the tracking of the negative effects of the environmental damages caused by manufacturing and analyze the manufacturing supply chain processes to better identify potential points of intervention; as well as the need for more external financial and technical resources to expand these projects.
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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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