Sociodemographic and Population Exposure to Upstream Oil and Gas Operations in Canada
Bibliographic record
Abstract
Canada, as one of the largest oil and gas producer in the world, is responsible for large emissions of methane, a powerful greenhouse gas. At low levels, methane is not a direct threat to human health; however, human health is affected by exposure to pollutants co-emitted with methane. The objectives of this research were to estimate and map pollutants emitted by the oil and gas industry, to assess the demographic of the population exposed to oil and gas activities, and to characterize the impact of well density on cardiovascular- and respiratory-related outcomes with a focus on Alberta. We estimated that ~13% and 3% people in Alberta reside, respectively, within 1.5 km of an active well and 1.5 km of a flare. Our analysis suggests that racial and socioeconomic disparities exist in residential proximity to active wells, with people of Aboriginal identity and people with less education being more exposed to active wells than the general population. We found increased odds of cardiovascular-related (1.13-1.29 for low active well density) and respiratory-related (1.07-1.19 for low active well density) outcomes with exposure to wells. Close to 100 countries produce oil and gas, making this a global issue. There is an important need for additional studies from other producing jurisdictions outside the United States.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".