The Construction of an Environmental Management Model Based on Sustainability Indicators on a Higher Education Institution in Mexico
Bibliographic record
Abstract
Without depreciating the importance of environmental regulations directed to university environmental managements systems in this country, nowadays, the instruments of international importance like the Sustainable Development Goals or ONU’s 2030 Agenda; as well as those of domestic nature, like sustainability indicators proposed by the Mexican Consortium of University Environmental Programs for Sustainable Development (Complexus) to measure the contribution of Higher Education Institutions to sustainability (HES), and those indicated by the Interinstitutional Committees for Higher Education Evaluation (CIEES) and the organisms that make up the Council for the Accreditation of Higher Education (COPAES), pose great challenges to universities as institutions that form human capital who are aware of their relationship with nature.This forces the university to rebuild its sustainability view based on the premise that all activities relative to its substantive functions are related to socio-environmental issues on the region.Due to this, Universidad Autónoma de Baja California (UABC), coherent to its environmental management institutional plan, defined in the Institutional Development Plan, must structure a series of indicators which allow the evaluation of its sustainability policy.The purpose of this research is to develop an environmental management model bound to performance indicators that allow UABC to progressively assume the task of answering the environmental challenges posed by its surroundings, trying to strengthen its curricula, in order for its programs to be more relevant and appropriate with social, economic, cultural, and environmental priorities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".