Trade and Industrial Policy as Levers for Sustainable Energy Technology Adoption? Experiences from Urban<scp>L</scp>atin<scp>A</scp>merica
Bibliographic record
Abstract
Abstract Debates abound regarding the link between trade and industrial policy and the adoption of sustainable energy technologies in developing countries. Some purport that open trade regimes support technology diffusion, while others indicate that more interventionist regimes are more conducive. This paper uses empirical evidence from Mexico City and São Paulo to argue that sustainable energy technology uptake can be more prevalent in settings with partially open trade policy regimes. These regimes have afforded countries more opportunities to develop local capabilities, which, in turn, has had knock‐on effects on sustainable energy technology uptake. Specifically, having more local technology sources (equipment, expertise) brought quicker access to these technologies, created more perceptions of technology “ownership,” fostered more effective mobilization, and helped create well‐established standards, which in turn contributed positively to sustainable energy technology uptake, while taxes and tariffs were less influential.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".