Bibliographic record
Abstract
The deregulation of Alberta’s electricity market was focused on providing consumer choice and shifting the risk burden of investment from the public to the private sector. However, Alberta’s deregulated retail market has been distorted by the existence of the Regulated Rate Option (RRO); an electricity rate plan based on consistent, flat per-kWh pricing. With two-thirds of Albertans remaining on the RRO - thanks in part to its use as the default rate plan - inefficiencies permeate throughout the Province’s electricity market. Under flat rate pricing schemes, price signals from the market are not delivered to consumers, and consumers do not adjust consumption even when its marginal cost far outweighs the price they pay. This exacerbates periods of limited supply and results in higher overall pool prices. The effect on the profile of daily demand - known as the load curve - is larger “peaks” in demand, where prices are highest. Eliminating or reducing these peaks could result in lower overall pool prices, enhanced system reliability, lower emissions, fewer public investments in infrastructure, and fewer abuses of market power. Even small reductions in load can translate to large reductions in the pool price, as the pool price increases exponentially in reaction to a linear increase in load.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".