Potential for an improved pesticide regulatory system in Mexico
Bibliographic record
Abstract
Hazards arising from an increase in the use of pesticides in Mexico have stimulated the development of a complex pesticide regulatory system, comprising inter-institutional participation of four governmental Secretariats.However, because this arrangement has not been reformed, despite several analytical reviews, since its creation almost 20 years ago and evidence of environmental and health damage by pesticides has continued to increase there is concern about its effectiveness.This thesis focuses on the proposal to improve the regulatory system for pesticides in Mexico.The regulation is covered by a patchwork of laws which are not integrated into a single structure.The analysis of the current system showed few gaps in the legal framework but its implementation and enforcement have been slow and difficult.The narrow achievement of the objectives of the Inter-Secretarial Commission for the Control of the Processing and Use of Pesticides, Fertilizers and Toxic Substances (CICOPLAFEST), as a coordinating body of the regulation of pesticides and other hazardous substances, also denotes clear organisational and administrative limitations.Considering the political, administrative and economic context of Mexico and the main objectives of pesticide stakeholders, the leadership of the Health Secretariat (SSA) on pesticide control through the concentration of the main regulatory activities in the Federal Commission for the Protection against Health Risks (COFEPRIS), the creation of an exclusive law for pesticides and the presence of a reformed CICOPLAFEST were found to be the way to improve the regulatory system most appropriately within the range of objectives identified and defined.This work supports the view that legislation is the short-term solution to the range of pesticide problems; hence the new law would provide strong foundations and clarity to the regulation of pesticides.It is also considered that institutional factors can have a decisive influence to promote an intensive use of pesticides; thus it is expected that the leadership of SSA would provide a balance in the public policies as the current subsidy to pesticides is a clear incongruence with policies on protection of human health and the environment.Along with these strategies other initiatives are supported, such as the strengthening of training and education, closer contact with the scientific community, encouragement of the use of less toxic pesticides, among others, which would constitute the long term solution to pesticide problems.A set of indicators is also proposed to measure the adequacy or inadequacy of this proposal, which would provide the basis for a continue improvement.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".