Indicators of sustainable development for catchment management in South Africa - Review of indicators from around the world
Bibliographic record
Abstract
Indicators are the ideal means by which progress towards sustainable development can be measured. However, most indicator initiatives throughout the world have been aimed at state-of-the-environment reporting, with relatively few aimed at developing sectoral indicators. This paper provides the results of a review to establish trends in the development of indicators that assist in integrated water resource management. Twenty-one organisations from around the world were approached with regard to whether they had developed indicators of sustainable development for catchment management. Of these, only five organisations had developed, or were in the process of developing, indicator sets that were available for review. These included the Fraser Basin Council (Canada), the Murray-Darling Basin Commission (Australia), the Tennessee Valley Authority (USA), the United States Environmental Protection Agency and the World Resources Institute. All of these indicator sets were developed using an issuesbased approach. Each indicator set was unique, reflecting the policy, both national and organisational, upon which it had been based. An analysis of these five indicator sets revealed that the most important themes that required information for water resource management at a catchment level, were biodiversity and ecosystem integrity, land-use change, water quality, waste production, water availability and resource use. Common indicators included population growth; community involvement; water availability; water use; water quality trends; soil contamination; non-compliance; species at risk; key species assessment; change in vegetation; agricultural impact; access to recreational opportunities, and ecosystem health. The identification of these themes and common indicators will be useful for the development of indicators for catchment management in South Africa. More importantly, policy frameworks and the physical characteristics of catchment systems in the country need to be taken into account. Additionally, it is recognised that no effective indicator set can be developed without the input of stakeholders. WaterSA Vol.27(4) 2001: 539-550
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.028 | 0.039 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".