Bibliographic record
Abstract
Over the past 130 years, electrical safety design and safe work practice standards have evolved around the world. In some instances, they are similar, and in other cases interesting variations have been observed. Numerous papers previously presented at this workshop have discussed electrical safety programs and challenges in several countries, and IEEE associated electrical safety workshops have occurred in several countries, including the U.S., Canada, India, Brazil, and Costa Rica. The IEEE IAS Electrical Safety Committee has set goals to broaden involvement in electrical safety to embrace electrical safety worldwide. In addition, recent papers and discussions have brought forth the varying cultures on implementing electrical safety and how this likely affects safety performance. Electrical safety includes design and safe work practices in utility power, facility power, utilization equipment, and specialized equipment. We are most familiar with those in the U.S. and Canada, including, respectively, NESC, NEC, NFPA 70E, UL, and DOE Guidelines. However, there are numerous equivalencies outside the U.S. including, for example, IEC, TUV, ETL, and other similar standards, including many unexplored standards in Japan, Russia, Brazil, and China. With ever more industrial globalization, the exploration and understanding of electrical safety standards around the world becomes more significant so that we can share and evaluate best practices from all countries. Some examples of global industries are wind energy, chemical, transportation. The study will also increase communication and collaboration worldwide. This paper explores and summarizes the design and safe work practices of the top leading technological countries, including, at a minimum, the U.S., Canada, European Union, Brazil, Russia, Japan, and China. It will also discuss cultural differences that may affect electrical safety. Areas covered include utility and facility power, component and equipment standards, and specialized equipment, such as R&D and energy storage. The purpose will be to stimulate international collaboration and appreciation of the diversity worldwide, in electrical safety.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.553 | 0.499 |
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".