Bibliographic record
Abstract
Creating a regulatory framework for network sectors such as electricity in developing countries is constrained by lack of regulatory expertise and capital for expansion, a potentially high regulatory burden relative to the size of the sector, small but growing markets and low incomes. Regulatory models designed for electricity sectors in developed economies may not be suitable for developing economies or require serious reengineering to be effective. Unless a number of preparatory measures are in place, any attempt to implement a regulatory regime or reform of a current system is unlikely to succeed if the objective is to create a self-sustaining electricity sector in support of economic growth rather than a drain on budgetary resources. In this paper, five basic regulatory models are outlined with a focus on regulatory objectives and necessary conditions for success. The next section of the paper then illustrates the characteristic steps in the process of transformation from a vertically integrated and publicly administered utility towards a self-sustaining electricity sector directed by market-based incentives and signals in a hypothetical developing country, The associated policy choices at each stage of the process are identified and conclusions drawn regarding possible interim regulatory frameworks. The last section of the paper highlights the considerations in designing a long-term regulatory governance system in a developing country reflecting the presence and/or absence of factors more pertinent to systems in the developed world with a view to designing an efficient and cost effective regulatory process.
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 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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".