Multiregulation in Developing Countries
Bibliographic record
Abstract
The question of multiregulation in developing countries has many dimensions. We investigate in this paper the lessons that can be derived from the Theory of Organizations, as well as from the past and present experience of a number of countries. The main issues considered decentralization, sectorial specialization, and functional specialization. For instance, should we have in federal states a federal regulation or should we decentralize regulation in each state? should we recommend a federal regulation of telecommunications in Brazil or a two-tier system of state and federation regulation as in the USA or the European Union? Or, for the regulation of electricity, should we recommend a regulation at the level of Sub-Sahara West Africa rather than national regulations? Second, what is the desirable industrial scope of a regulator, or how many industries should a regulator supervise? Should we have one regulator per industry or a regulator for all industries as in Panama, Jamaica, Costa Rica or at the state level in USA, Canada, Australia and Brazil? Should the optimal design evolve over time as the recent integration of gas and electricity regulations in the U.K. might suggest? Third, regulation has several functional dimensions, including regulation of prices, quality, environmental effects,etc.
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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 | 0.003 | 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 | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".