Constructive engagement and negotiated settlements - a prospect in the England and Wales water sector?
Bibliographic record
Abstract
UK utility regulation initially aimed to avoid the perceived disadvantages of the US approach. The typical UK price control review now involves a substantial consultation process, led by the relevant regulator. Plans put forward by the utilities are analysed and discussed, including with other interested parties. The regulator then determines allowed revenue for the next period of years. This determination usually includes an explicit or implicit view on an efficient and appropriate future investment programme. In these respects, practice is more flexible and less legalistic than the traditional US regulatory approach. But there is also greater regulatory involvement. In contrast, some jurisdictions in the US and Canada have effectively moved in the opposite direction. Utilities and interested parties, especially users and consumer representatives, seek to negotiate a settlement of some or all of these matters between themselves. The regulatory commission normally approves such a settlement provided that all interested parties have had an opportunity to be involved and are in support, and provided the settlement is consistent with the commission’s statutory duties. The traditional regulatory process operates only in the event that the parties fail to agree. Some UK regulators have expressed concerns about the UK regulatory process and indicated an interest in this alternative approach. 1 One UK regulator has already moved in that direction. To avoid the problems and acrimony of the previous price control review, the Civil Aviation Authority (CAA) encouraged the airports and airlines to engage in a process of ‘constructive engagement’ on a specified set of inputs to the price control review. They did so, and managed to agree substantially on quality of performance standards, traffic forecasts and the investment programme at Heathrow and Gatwick. The All Party Parliamentary Water Group (APPWG) recently said that it “would like to explore these approaches in the UK and the possibility of a potential role for
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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 | 0.061 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.037 |
| Scholarly communication | 0.035 | 0.030 |
| Open science | 0.005 | 0.044 |
| Research integrity | 0.022 | 0.016 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".