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Record W2999624664

Oil Sands and the Earth

2008· book· en· W2999624664 on OpenAlexaboutno aff
Babiuk Colin

Bibliographic record

VenueVDM Verlag Dr. Müller eBooks · 2008
Typebook
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsLeaseRevenueGovernment (linguistics)Greenhouse gasResource (disambiguation)Natural resource economicsOil sandsPolitical scienceEnvironmental resource managementBusinessEconomyGeographyEnvironmental planningEnvironmental scienceEconomicsFinanceEcology
DOInot available

Abstract

fetched live from OpenAlex

The Alberta Government posted record budget surpluses in 2005 and 2006. Revenues were attained primarily through record non-renewable resource revenues. Oil sands development as the major economic driver of Alberta?s economy and accounts for 62 per cent of major projects. The processes used to develop and extract energy from the oil sands, mining and in-situ recovery, are also known to be the most harmful to the environment with damage ranging from habitat destruction, depletion of freshwater reserves and the production of large amounts of greenhouse gas emissions. Despite the known negative impact on the environment, record numbers of megaprojects and new lease agreements are being processed. Critical praxis theory and critical discourse analysis methods are utilized to examine how stakeholders frame issues in the news media to create and shape public perception of the environmental impact of energy development in Alberta, Canada. This book aims to contribute to the field of discourse analysis by gaining a deeper understanding of how discourse is used to argue and support an argument in the print news media.

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: Other · Consensus signal: Other
Teacher disagreement score0.537
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.006
Scholarly communication0.0090.002
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.009
GPT teacher head0.170
Teacher spread0.161 · 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
GenreOther

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
Published2008
Admission routes1
Has abstractyes

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