Institutional or structural: lessons from international electricity sector reforms
Bibliographic record
Abstract
Introduction The widespread privatization of national electricity sectors across both the developing and developed world provides a broad base of experience to assess the relative performance of various countries in attracting private sector participation in the industry. Since 1980, when Chile commenced a radical restructuring, and later privatization program, over sixty countries have introduced reforms in the electricity sector. These reforms have been generally designed with the purpose of increasing the levels of private ownership and investment, thereby reducing the dominance of the state-owned vertically integrated enterprise, the traditional mode of organization. There is substantial variability in the nature of these reforms. Some countries have invited private investment in the generation sector only, financed by long-term supply contracts to state-owned utilities (e.g. China, India, Indonesia, Mexico); some have vertically separated the industry but privatized only part of the sector (e.g. Colombia, El Salvador, Kazakhstan, New Zealand); while others have privatized the entire industry and additionally created competitive generation markets (e.g. Argentina, Chile, United Kingdom). The degree of private sector interest, however, has been markedly mixed across countries. There have been some notable successes in attracting significant levels of private investment in all sectors of the industry (e.g. Argentina, Australia, United Kingdom). On the other hand, private investors have shown little interest in purchasing state-owned enterprises or in financing de novo infrastructure assets in countries such as Mexico, Turkey, or the Ukraine, to name only a few. Indeed some countries, including Hungary and Venezuela, have had to postpone planned privatization programs owing to lack of investor interest.
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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 | 0.004 |
| 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 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".