[Blog] Worried about high energy bills, some Canadians risk discomfort, illness and even death
Bibliographic record
Abstract
Almost one in 10 Canadian households spend more than 10 per cent of their income to heat and cool their homes, keep the lights on and to store or cook food. For these households, the high cost of energy, which includes electricity, natural gas, heating oil and propane, means they may ration their use, leading them to live in energy poverty. Energy, in its many forms, has a vital role in people’s lives. It can provide entertainment, nourishment and the ability to work, but it also supplies critical services, such as heating or cooling. Extreme weather events, like the 2021 heat dome in Western Canada, are expected to increase in frequency in the future and will amplify the need for these critical energy services. A household’s high energy burden could be a risk to the lives of everyone in that home. Our research shows that some households in Canada spend up to 16 per cent of their household budget on energy — almost five times more than those who do not live in energy poverty. It strongly suggests that many households in Canada are struggling to meet their basic energy needs.
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 | 0.000 | 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 | 0.010 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.221 | 0.031 |
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".