Benefits, costs and enabling conditions to achieve ‘water for all’ in rural and remote Australia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Australia will not meet Sustainable Development Goal target 6.1, to “achieve universal and equitable access to safe and affordable drinking water for all” by 2030, unless water service provision is improved to hundreds of small (less than 10,000 residents), rural and remote (SRR) communities. We have estimated the national benefits of a programme to upgrade drinking water services to ensure ‘good quality’ for 395 Australian SRR communities using a stated preference survey of 3,523 participants reflective of the Australian population. Using multiple model estimates, we calculated the willingness to pay at between AU$324 and AU$847 per Australian household per year for 10 years. Aggregating across the relevant Australian population, we calculated the aggregate willingness to pay for water quality improvements at AU$1.2–4.7 billion yr −1 , or AU$8.3–33.2 billion as a 10-year net present value. We further estimated the capital and operating costs to provide ‘good-quality’ drinking water in the 395 SRR communities under three scenarios; the costs range from AU$0.51 to AU$3.29 million per community and, in total, from AU$0.2 billion to AU$1.3 billion.
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.
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 | 0.000 | 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 it