Natural Gas Development: Extracting Externalities - Towards Precaution-Based Decision-Making
Bibliographic record
Abstract
In recent years, natural gas has become an increasingly important energy resource throughout North America. As demand for natural gas continues to rise, the continent has experienced an unprecedented expansion in the resource’s extraction and development. This increase in development activities has given rise to the potential for greater adverse environmental and human health impacts. Only recently have comprehensive studies evaluating the potential environmental and health effects of extraction techniques, including hydraulic fracturing, begun to be published; there is now compelling evidence that natural gas development poses significant threats to the environment and to human health. Despite these emerging studies, there continues to be considerable informational gaps regarding increases in air pollution, contamination of water resources from the complex mixture of chemicals used in natural gas development, and the subsequent adverse effects on ecosystems and the health of humans and other species. These gaps in information make effective regulation of development activities difficult to achieve. Faced with growing public concern regarding the environmental contamination associated with natural gas development, many states, provinces, and municipalities across the United States and Canada have begun to implement precautionary-based moratoriums and other preventative legislative and regulatory measures to protect communities against probable adverse effects. Preventative approaches have varied greatly, from modification of municipal zoning laws to state- and provincial-level moratoriums on hydraulic fracturing, or in the case of the Province of Quebec, an anticipated halt to all future shale gas development activities. While there may be no one-size-fits-all solution appropriate for all jurisdictions, we argue that successful and effective regulation of the industry may prove impossible without greater understanding of the interaction between development, exploration, the environment, and human health. Currently, we are far from comprehending the full extent to which unprecedented natural gas development is affecting the environment. Hence, we maintain that moratoriums on natural gas development are necessary until such time it can be determined that the activity will not present significant risks to human health, ecosystems, and the surrounding environment.
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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 | 0.030 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".