MétaCan
Menu
Back to cohort
Record W3173284332 · doi:10.1680/jenes.21.00023

Canada’s oil sands industry from a sustainability perspective

2021· article· en· W3173284332 on OpenAlexaffvenueabout
Nima Khakzad, Mohammad Dadashzadeh, Rouzbeh Abbassi, Ming Yang

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2021
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSustainabilityOil sandsLand reclamationNatural resource economicsRevenueBusinessDisturbance (geology)Petroleum industryEnvironmental resource managementEnvironmental protectionEnvironmental planningGeographyEnvironmental scienceEconomicsEcologyEnvironmental engineering

Abstract

fetched live from OpenAlex

The present study aims to investigate the impacts of oil sands development in Canada on the economy, society and the environment as the three pillars of sustainability. Factors such as aquatic ecosystems, land disturbance and reclamation, air quality, public health, safety, aboriginal and local communities, gross domestic product, employment rate and job creation, government revenues and demographic changes have been considered. Based on a review of the available literature, this study shows that the oil sands industry has so far fallen short in keeping a balance among the three pillars of sustainability, with the negative impacts on society (e.g. changing the lifestyle of Aboriginal people) and the environment (e.g. land disturbance) overweighing the relatively positive economic impacts. This, along with the current pace of remedies (e.g. land reclamation), makes it hard to conclude that the oil sands industry is sustainable.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.002
Scholarly communication0.0050.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.212
Teacher spread0.208 · 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 designNot applicable
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

Citations5
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Environmental Engineering and ScienceSame topicGlobal Energy and Sustainability ResearchFrench-language works237,207