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
Prior to Mexico's entry to the North American Free Trade Agreement (NAFTA), predictions of the consequent impact on the environment in that country ranged from the dire to very optimistic. This article investigates NAFTA's outcomes in terms of energy use and the emission of atmospheric pollutants. Specifically, has entry into NAFTA led to a convergence or divergence in indicators of emissions, environmental efficiency, and emissions‐specific technology in Mexico, the United States, and Canada? A battery of tests is applied to these indicators for energy use and carbon, sulfur, and NOx emissions in the three countries. The results show that the extreme predictions of the outcomes of NAFTA have not materialized. Rather, trends that were already present before the introduction of NAFTA continue and, in some cases, improve post‐NAFTA, but not yet in a dramatic way. There is strong evidence of convergence across the three countries toward a lower intensity of energy use and emissions per unit of GDP. Although intensity is rising initially for some variables in Mexico, it eventually begins to fall post‐NAFTA. Per capita emissions of sulfur and NOx also show convergence, but this is not the case for energy and carbon, and the latter variables also drift moderately upwards. The state of technology in energy efficiency and sulfur abatement is improving in all countries, although there is little, if any, sign of convergence and NAFTA has no effect on the rate of technology diffusion. However, total energy use and carbon emissions increase both pre‐ and post‐NAFTA and total NOx emissions increase in Mexico. Only total sulfur emissions are stable and falling in all three NAFTA partners.
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 | 0.000 |
| 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