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Record W2885742462 · doi:10.4337/9781784712303.00009

Environmental and Indigenous issues associated with natural gas development in British Columbia

2018· book-chapter· en· W2885742462 on OpenAlexaboutno aff
Anna Vypovska, Laura A. Johnson, Dinara Millington, Allan Fogwill

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2018
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousWildlifeEnvironmental planningThreatened speciesEnvironmental impact assessmentGreenhouse gasNatural resourceEnvironmental resource managementCumulative effectsGeographyEnvironmental protectionNatural (archaeology)Political scienceEnvironmental scienceHabitatEcologyLawArchaeology

Abstract

fetched live from OpenAlex

This chapter discusses key environmental and Indigenous peoples’ issues facing development of the natural gas and liquefied natural gas (LNG) industry in the Province of British Columbia, and examines the main approaches to mitigate, manage and monitor these issues effectively. The authors reviewed environmental assessment applications for 29 major natural gas and LNG projects in British Columbia that have undergone a typical environmental assessment process with the provincial or federal responsible authorities since 2010, as well as the content of primary regulatory documents and issues identified in relevant case law. The key environmental issues identified from the review include significant residual adverse effects related to greenhouse gas emissions; significant residual adverse effects and cumulative effects to rare and threatened wildlife species; and cumulative adverse impacts of natural gas development. The most common potential adverse impacts on Indigenous peoples’ interests summarized in the review include but are not limited to effects on health and socio-economic conditions; physical and cultural heritage; the current use of lands and resources for traditional purposes; sites of historical and archeological significance; and potential cumulative impacts on Aboriginal interests. The chapter also provides examples of key approaches to mitigate the foregoing issues and stresses the importance of effective consultation and engagement with Indigenous groups at early stages of the proposed projects development.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.255
Teacher spread0.238 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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