Transportation Impacts of Fracking in the Eagle Ford Shale Development in Rural South Texas: Perceptions of Local Government Officials
Bibliographic record
Abstract
This paper explores the impacts on transportation infrastructure and transportation-related issues associated with the gas and oil boom in the Eagle Ford Shale region in rural south Texas. It begins with a general explanation of fracking and its general impacts along with specifics of the Eagle Ford Shale region. Drawing on data gathered both from crash trends and two surveys administered to public officials in the Eagle Ford Shale region, we present a description of the impacts of fracking on cities and counties. Crash trends between 2009-2013 overall show a 26 percent increase. Fatalities and severe injuries also increased by 49 percent. The survey results show that counties and cities are experiencing significant challenges in meeting increased demands placed on their transportation system by fracking including increased traffic and congestion, deteriorating roads, and increased cost of maintenance. Keywords: fracking, transportation policy, energy resources, rural traffic, oil ----------------------------------------------------- Cet article examine les effets sur les infrastructures de transport et les problemes lies au transport suite au boom economique de l'industrie du petrole et du gaz, dans la region de Eagle Ford Shale, dans le sud rural du Texas. Il debute avec une explication generale de la fracturation, de ses impacts globaux et specifiques a la region de Eagle Ford Shale. En utilisant les donnees recueillies des tendances d'accidents et de deux enquetes administrees a des fonctionnaires dans la region de Eagle Ford Shale, nous presentons une description des impacts de la fracturation sur les villes et les comtes. Les tendances des accidents montrent globalement une hausse de 26%, entre 2009 et 2013. Les fatalites et les blessures graves ont aussi augmente de 49%. Les resultats de l'enquete montre que les comtes et les villes experimentent des defis significatifs face aux demandes croissantes faites dans leurs reseaux de transport par la fracturation, incluant le trafic et la congestion accrus, la deterioration des routes et l'augmentation des couts de maintenance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".