An assessment of the feasible application of environmental valuation methods on Rand Water open-space
Bibliographic record
Abstract
Rand Water has contracted University of South Africa (UNISA) to develop a monetary valuation method for its open spaces and its inherent ecological functions. This article begins by reviewing existing contemporary definitions for open space in South Africa and then identifies the key characteristics thereof. Open Spaces in the Gauteng urban environment is in a crisis and factors such as open space coverage standards, sale of open space, crime and the impact of the apartheid legacy are briefly examined. Rand Water’s open space contributes to the total open space stock of Gauteng province. Any shortage of open space and threats to the sustainable management and expansion of the open space network of the province therefore has a direct bearing on howRand Water views and manages its open space resources. Environmental resource economics provides economists and environmentalists with various instruments to place a monetary value on the environment. The available valuation instruments are briefly reviewed and questionnaires are developed from this to determine whether it can be applied by Rand Water staff to obtain values at a minimal cost, in a short space of time, and whether it assesses the various use and non-use values.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".