A Review of Fracking's Global Footprint: Environmental Consequences and Regulatory Landscapes
Bibliographic record
Abstract
Fracking (hydraulic fracturing), an innovative drilling technique used to extract unconventional oil and gas, has raised significant global concerns due to its environmental and social impacts. This review analyses the environmental consequences of fracking, focusing on methane emissions, groundwater contamination, social challenges, and the regulatory frameworks governing these operations. To achieve these objectives, we conducted a comprehensive desk-based literature review to assess the global effects of fracking in different countries and regions. Our findings indicate that: (1) Fracking has not been universally adopted, with only a few countries like the United States, Canada, Argentina, and China practicing it extensively; (2) Several countries, such as France, Germany, and Ireland, have imposed bans or strict regulations due to its negative environmental impacts; (3) Despite its high risks, fracking has yielded significant benefits, such as increased oil and gas production and reduced energy dependence; and (4) Local communities in many regions have protested against fracking due to threats to environmental sustainability, especially groundwater resources. We recommend that fracking operations be limited to areas with minimal or no human habitation to mitigate its effects on public health and environmental quality.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".