Earth, Wind, and Fire: Power Infrastructure in Alberta’s New Age
Bibliographic record
Abstract
In the wake of dramatic policy changes commencing in late 2015, including the Government of Alberta’s announcement of the Climate Leadership Plan, the Renewable Energy Program, and the decision to introduce a parallel capacity market into Alberta’s previous energy-only market, the future of Alberta’s electricity market is uncertain. However, regulatory intervention in an attempt to improve the function of electricity markets and encourage renewable generation is not a new concept.Other jurisdictions, including the United Kingdom, Germany, and jurisdictions in the United States, have used regulatory intervention to address issues in energy markets and to drive renewable generation. Regulatory intervention in these jurisdictions has not always achieved the intended consequences. In some cases, regulatory intervention has exacerbated issues it intended to solve, or created new problems. In other cases, regulatory intervention has relatively improved the function of electricity markets and incited renewable generation. This paper considers the evolution of energy policy and competing policy drivers, including system reliability, use of sustainable fuels to generate electricity, and price surges. The paper will discuss the success and failure of regulatory intervention in select jurisdictions, and how these lessons might apply in the new age of Alberta’s electricity market.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".