Water Supply in California: Economies of Scale, Efficiency, and Privatization
Bibliographic record
Abstract
In a water supply industry that consists of private and public providers, questions of interest include the following: Are there significant economies of scale, and if so at which population levels' How, on average, do private and public sector rates compare? Has there, over time, been a systematic change in the gap between private and public sector rates' Can it be demonstrated that investor owned companes are more efficient than their public sector counterparts' Given major differences in taxes and subsidies, is the real water bill for government owned utilities higher than for investor owned companies' The first three questions will be answered by a statistical analysis of water charge data collected by Black and Veatch Corp. on a biannual basis for the period 1995-2001. The remaining two questions received affirmative answers in a 1996 study commissioned by the Reason Foundation, a conservative think tank located in Los Angeles. The current paper reexamines the last two questions in light of a broader literature on privatization, and by drawing on the more extensive and more representative data set referred to above. The findings and conclusions reached in this paper provide a new and quite different perspective on the fundemental questions as to who should supply the consumers water. In the past communities have opposed proposals for privatization because of concerns over whether the Public Utilities Commission would, or would be able to, keep water rates at acceptable levels. The present paper also sheds light on this question.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".