Public Health and Unconventional Oil and Gas Extraction Including Fracking: Global Lessons from a Scottish Government Review
Bibliographic record
Abstract
Unconventional oil and gas extraction (UOGE) including fracking for shale gas is underway in North America on a large scale, and in Australia and some other countries. It is viewed as a major source of global energy needs by proponents. Critics consider fracking and UOGE an immediate and long-term threat to global, national, and regional public health and climate. Rarely have governments brought together relatively detailed assessments of direct and indirect public health risks associated with fracking and weighed these against potential benefits to inform a national debate on whether to pursue this energy route. The Scottish government has now done so in a wide-ranging consultation underpinned by a variety of reports on unconventional gas extraction including fracking. This paper analyses the Scottish government approach from inception to conclusion, and from procedures to outcomes. The reports commissioned by the Scottish government include a comprehensive review dedicated specifically to public health as well as reports on climate change, economic impacts, transport, geology, and decommissioning. All these reports are relevant to public health, and taken together offer a comprehensive review of existing evidence. The approach is unique globally when compared with UOGE assessments conducted in the USA, Australia, Canada, and England. The review process builds a useful evidence base although it is not without flaws. The process approach, if not the content, offers a framework that may have merits globally.
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 | 0.037 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".