End-user Electric Demand Management Should be a National Policy Objective
Bibliographic record
Abstract
ABSTRACT An effective national energy policy must include a broad array of approaches to meeting the nation's energy needs. The more energy arrows in the quiver, so to speak, the better we may meet the challenge. As it has evolved over the past 25 years, our energy policy has reflected mounting awareness that we must address both the need to increase energy supply and the need to curb the growth in energy demand. Yet the application of attention and resources to these complementary efforts has been uneven. Energy supply issues are often at the forefront of political discourse and public awareness, and supply-side initiatives tend to generate the lion's share of funding. As to the various techniques of demand-side management (DSM), however, the pronouncements of policymakers have not always kept pace with technological advancements that stand to vastly improve the effectiveness of such techniques. Time-of-use energy pricing, in particular, could become a far more potent DSM tool as a result of innovations in metering technology. Despite the past relative neglect of such matters, there are encouraging signs in proposed federal legislation and ongoing federal and state regulatory initiatives that DSM in general, and time-of-use energy metering and pricing in particular, may finally have their day.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".