Going more private and sustainable: ex-post assessment of armenian water utilities
Bibliographic record
Abstract
Recent worldwide changes in water policies emphasize the role of the private sector in the provision of water services with the expectation of market forces to redress public provision failures and introduce innovative approaches for promoting sustainability.Armenia has experienced unprecedented rapid and mass privatization in the water sector: in a decade from zero reaching 63% of the population, which records the third highest level in Europe.The paper examines the impacts of privatization on sustainability performance of all water utilities.Ex-post benchmarking is employed for assessing relative and absolute sustainability measures and developing scores for utility sustainability ranking.The paper focuses on utility performance in time and scale dimensions and on the international level.The paper shows that transition to the public-private partnerships positively influenced the sustainability performance of all utilities.All utilities have improved their relative to pre-privatization performance.Considerable progress was seen in social followed by environmental performance.Armenian utilities also succeed in performing well internationally.The paper concludes that though water privatization may lead to sustainability of utility performance, the scale of impact may depend on the initial state of the enterprise and the local context.Moreover, after the low-hanging fruits are reached at the first stage, more efforts will be required for enhancing long-term sustainability and effectiveness, consistent with social and environmental needs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".