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Record W2748393751 · doi:10.1071/aj10076

Global environmental review processes for oil and gas projects*

2011· article· en· W2748393751 on OpenAlexaboutno aff
Bill Gorham

Bibliographic record

VenueThe APPEA Journal · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental impact statementEnvironmental impact assessmentCommonwealthEnvironmental planningScale (ratio)EngineeringScope (computer science)Liquefied natural gasBusinessEnvironmental protectionEnvironmental resource managementEnvironmental sciencePolitical scienceWaste managementNatural gasGeography

Abstract

fetched live from OpenAlex

The environmental review processes for major oil and gas projects vary significantly worldwide. Three LNG projects in WA (Gorgon, Browse and Wheatstone), one in NT (Ichthys), four in Queensland (Queensland Curtis LNG, Gladstone LNG, Australia Pacific LNG and Shell Australia LNG), and one in Commonwealth waters (Prelude) have all experienced—or are in the midst of—the Australian environmental review processes. The foundation of the environmental review of these projects is anchored in existing state and federal statutes and regulations, but the application to each project varies according to the specific characteristics of each proposal. Similar large scale LNG projects in other countries are subject to analogous processes. Some are as rigorous as those in Australia but there are also some with less well-developed environmental review processes. In the latter cases, either corporate and/or financial institution standards dictate the environmental review processes. This extended abstract reviews the processes that the present above-mentioned LNG projects have gone through or are going through and compares them to similar processes in other countries where large-scale oil and gas projects have been proposed or permitted. The authors compare both the strategic assessment approach taken for the Browse LNG project to the more traditional approach of environmental impact statement/environmental review and management plan used for other recent or present oil and gas projects. The authors also evaluate these reviews in relation to comparable multi-jurisdictional reviews taken in the US, Canada and the UK for their joint federal/state/regional environmental review processes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.031
GPT teacher head0.274
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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