Efficiency and Compliance Regulations: Side Effects
Bibliographic record
Abstract
Abstract Beginning in 1992, the U.S. and Canada enacted efficiency standards forindustrial electric motors and other electrical components. Over the years, thescope of these regulations continues to raise the level of efficiency and alsowiden the coverage across motors 1 – 500 horsepower. Other countries arefollowing the lead of North America and establishing their own standards. As we mandate premium efficiency levels, many incentive programs have beendiscontinues because of "free ridership". This may result in more old lessefficient motors being rewound rather than replaced with premium designs. Testing in North America must be done by a certified lab but this is notnecessarily the case elsewhere. In some countries, the tests must be performedby a government lab, even though the motors were tested in a certified labelsewhere. These requirements may hamper U.S. exports and act as protection fordomestic manufacturers. Verification and compliance in the U.S. may not be working well. Electricmotors embedded in equipment are to comply with the Energy Policy Act of 1992(EPAct) and Energy Independence and Security Act of 2007 (EISA) regulations butmay not be getting the proper inspection. This may result in domestic machinerymanufacturers being at a disadvantage to imported goods. The impact on motor performance, on motor installation requirements, on powersystems as a whole, and on overall process efficiencies are discussed. On one hand we pass laws meant to reduce electricity use and carbon emissions, but the results are that they may have the opposite effect.
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 | 0.034 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.016 | 0.014 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".