An integral framework for sustainability assessment in agro-industries: application to the Costa Rican coffee industry
Bibliographic record
Abstract
Abstract The broad range of definitions for sustainability has led to the development of several sustainability evaluation frameworks that have emphasized facets of sustainability but have not encompassed all aspects found at the industry and regional level. The aim of this study was to address the broader issues of sustainability of agro-industrial systems. Rather than exclusively focusing on the environmental and social aspects of those economic activities that take place within the boundaries of industrial systems, it should be recognized that they belong to a broader system. The various types of sustainability are highlighted and current sustainability frameworks are evaluated. A comprehensive sustainability model that adequately takes into consideration the various types of sustainability within industrial systems was developed. The proposed framework considered indicators that provide descriptions of the systemic nature of industry and incorporates two-dimensional indicators instead of solely focusing on indicators that provide a one-dimensional, piecemeal evaluation of economics, environment, social and institutional sustainability. By evaluation of the boundaries of each arena, it provides comprehensive understanding of the system. The sustainability of the Costa Rican coffee industry within the context of the new framework is discussed. The framework presented integrates concepts such as industrial ecology and cleaner production, along with the more traditional EMS and social justice programmes, to promote sustainability. The development of employment and economic returns that benefit the local and regional systems through the generation of additional value-added products are promoted through the integration of eco-efficiency into the framework. Keywords: SUSTAINABILITYINDICATORSFRAMEWORKECO-EFFICIENCYAGRO-INDUSTRYCOFFEE INDUSTRY
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".