MétaCan
Menu
Back to cohort
Record W2193053980 · doi:10.5539/jms.v5n4p115

Issues Impacting Sustainability in the Oil and Gas Industry

2015· article· en· W2193053980 on OpenAlexvenueaboutno aff
Mohamad Danish Anis, Tauseef Zia Siddiqui

Bibliographic record

VenueJournal of Management and Sustainability · 2015
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilitySustainable developmentNatural resource economicsBusinessTriple bottom lineFossil fuelEnvironmental planningEconomicsEngineeringEnvironmental sciencePolitical scienceWaste management

Abstract

fetched live from OpenAlex

This research paper explores the concept of sustainability and the role played by O&G industry in achieving sustainable development. The authors bring a rational approach in defining the key issues for the O&G sector that affect sustainability as well as try to devise the inherent risks as well as mitigation approaches adopted by these companies. Sustainability is a topic gaining fast repute today. As new conventional oil and gas sources decline, unconventional sources, including shale gas in the US, oil sands in Canada, coal seam gas in Australia, and deep-water offshore wells in Brazil, West Africa and Asia have been identified as key areas with significant reserves potential. Despite the growth potential, sustainability risks such as climate change, safety risks, and community disagreements exert pressure on the economic feasibility of these opportunities. The three components of sustainable development: economic, environmental and social, often referred to as the ‘Triple Bottom Line’ or TBL, can be used in evaluating a company’s performance in financial, environmental and social dimensions. These three dimensions of sustainable development, as explained by John Elkington and adopted by Shell’s first sustainability report in 1997, are also commonly referred to as the 3Ps: People, Planet and Profit. The paper also focuses on analyzing the various threats that could obstruct sustainable development being carried out by companies in the oil and gas industry. The importance of sustainable economic growth with regards to the oil and gas industry has also been highlighted. The 3Ps explained above can be used to categorize the key issues/risks that impact sustainability. The researchers concluded that the sustainability programs followed by oil and gas industry are not satisfactory; however there is strong evidence of improvement in near future. Towards the end, the researchers have tried to list the Strategies and Methodologies for enhancing the effectiveness of sustainability strategies and programs for the sector.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.014
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0130.008
Open science0.0010.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.022
GPT teacher head0.321
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Management and SustainabilitySame topicGlobal Energy and Sustainability ResearchFrench-language works237,207