Assessment of the environmental sustainability of organic farming: Definitions, indicators and the major challenges
Bibliographic record
Abstract
Halberg, N. 2012. Assessment of the environmental sustainability of organic farming: Definitions, indicators and the major challenges. Can. J. Plant Sci. 92: 981–996. The debate over agricultural sustainability continues due to the challenges of reducing externalities of intensive farming methods and preserving vital natural capital, but many definitions of sustainability are too wide to allow for a prioritized assessment. This paper uses a more narrow definition of agricultural sustainability focusing on the functional integrity of a system to highlight specific aspects of vital importance for the long-term resilience and reproducibility of agricultural systems. Key areas of resource sufficiency are also identified. Based on a review of scientific literature the relative sustainability of organic agriculture is assessed with a focus on environmental impact and resource use in Europe and North America. While there are many examples of organic agriculture with improved performance in terms of soil fertility and preservation of biodiversity, in other aspects – such as resource use per kilogram product – the difference to conventional farming is less important. The paper presents a framework for selection of indicators based on the principles of organic agriculture which may be used to monitor and improve the performance of organic agriculture with respect to functional integrity and resource sufficiency. The differences between comparable organic farms may be used for improving farm practices through a benchmarking process.
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 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 | 0.024 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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 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".