Quantitative Assessment of Teleworking on Energy Consumption and Greenhouse Gas (GHG) Emissions
Bibliographic record
Abstract
Teleworking offers various socioeconomic benefits to society, but its environmental impact remains poorly understood.Using eleven participants from Ottawa, Canada, a year-long pilot study was designed and implemented to quantify energy usage and greenhouse gas (GHG) emissions in three domains: home office, transportation, and information and communications technology (ICT).The results show that transportation and home heating and cooling account for >94% of the energy associated with teleworking.Home office equipment, lighting, and ICT account for the remaining 6%, with an insignificant impact on GHG emissions (<2%) due to the low-carbon electricity grid.The results indicate teleworking will likely result in a net reduction in energy use and GHG emissions compared to conventional working arrangements due to reduced daily commute, especially when employees travel long distances to their company offices via personal vehicles.However, teleworking's net impact is highly variable, dependent on personal choices, routines, purchasing decisions, and household structure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".