The Future of Energy Regulation and Policy Development: A Summary Paper
Bibliographic record
Abstract
In September 2013, The School of Public Policy at the University of Calgary hosted 19 speakers and 55 delegates in Calgary for a full-day symposium entitled “The Future of Energy Regulation and Policy Development: Conflict, Compromise or Cooperation?” Participants included current and past regulatory officials at the federal and provincial or state levels in both Canada and the United States, academics, lawyers active in regulatory matters, and representatives from industry and non-governmental organizations. Symposium chair Michal Moore (Area Director, Energy and Environmental Policy at The School of Public Policy) challenged participants to imagine what the “next regulatory world” would look like and what we want the regulator of the future to look like, and to consider the future success of energy regulation. The discussion on the role and the future of the energy regulator was wide-ranging and thought-provoking. This paper summarizes the discussion and main themes; policy-related implications and observations arising from the symposium are presented in the conclusion.
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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.025 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".