NAFTA's Impact on Business Environmental Decision Making
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
Signing the North American Free Trade Agreement (NAFTA) liberalized trade policy and reduced tariffs between Mexico, the United States, and Canada, but activists opposed to the treaty predicted an environmental disaster. This article seeks to analyze the dynamics of environmental spending and changes in companies' profiles following NAFTA. Our results suggest that these predictions have not come true. Through an econometric model, we explore how 2,438 industries in the 1994–2002 period made environmental decisions and how much they spent on cleanup. Estimates were made with a dynamic panel model using the generalized method of moments (GMM) method. Our results suggest that environmental investment decisions depended on business size, their technological capabilities, sales performance, and the need to comply with the standards required by customers in the international market. The last section explores policies to improve compliance with Mexico's environmental regulations and to develop sustainable, eco‐friendly manufacturing.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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