Energy Savings in Industry: Canadian Industry Program for Energy Conservation
Bibliographic record
Abstract
The Canadian Industry Program for Energy Conservation (CIPEC) was established in 1975 and is the oldest voluntary industry and government energy efficiency partnership in the world. CIPEC is a sector-level outreach and advocacy program that: (1) promotes the establishment, implementation, tracking and reporting of energy efficiency improvement targets at an aggregate and sub-sector level, and (2) develops tools and services to overcome barriers to the implementation of energy efficiency programs and projects at the sector and company levels. CIPEC is delivered through the combined efforts of Natural Resources Canada and trade associations from the manufacturing, mining and electricity generation sectors representing over 8,000 companies and approximately 90% of secondary industrial energy use in Canada. This study reports on a process, market and impact evaluation of CIPEC. Key findings are as follows. (1) Estimates of net measure savings rates are based on a pre-post comparison of energy consumption using a control group. Savings by end use varied from a low of 1.7% of base consumption for facility lighting to a high of 5.6% of base consumption for process and water heating. About two-thirds of energy savings are attributable to electricity end uses while the remaining one-third of energy savings is due to fuel oil and natural gas. (2) Energy savings were estimated as the product of the use rate, the net savings rate, and the number of participants. Total savings over five years for CIPEC were some 28,178 TJ. (3) Carbon dioxide emission reductions were estimated as the product of energy savings by measure and a fuel specific emissions factor. Total emissions reductions for CIPEC were some 2,427 kilotonnes of carbon dioxide equivalent per year.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".