Shale Gas and Hydraulic Fracturing in the Great Lakes Region: Current Issues and Public Opinion
Bibliographic record
Abstract
This report presents the views of people living within the Great Lakes Basin regarding hydraulic fracturing and shale gas drilling. Hydraulic fracturing, the injection of a fluid after drilling to crack open shale rock to release oil or gas, has been used by industry for decades. However, recent breakthroughs in horizontal drilling techniques combined with hydraulic fracturing, have enabled oil and gas recovery from “unconventional” oil and gas reserves, previously considered inaccessible. This process is commonly known as “fracking,” which can refer to just the hydraulic fracturing process itself or the entire drilling process.As the developments in hydraulic fracturing and horizontal drilling technology have produced an increase in oil and gas supplies, many states in the US and provinces in Canada are trying to determine how to leverage the associated economic potential. In response to this rapid change in the energy landscape and the potential future energy portfolios of the US and Canada, this report serves to provide background on shale developments within the Great Lakes Region — Ontario, Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin — as well as a preliminary assessment of public opinion of fracking from residents within the Great Lakes Basin.This survey was part of a larger public opinion survey, which also assessed public views from the Great Lakes Region about environmental issues and policy in the Region as well as a closer look at policy related to wind power. These reports have been published by the Center for Local, State, and Urban Policy and are publicly available, among others, on related facets of this topic.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".