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Record W3161594906 · doi:10.1007/s11625-021-00969-0

Scenario planning tools for mitigating industrial impacts on First Nations subsistence economies in British Columbia, Canada

2021· article· en· W3161594906 on OpenAlexafffundabout
David Natcher, Naomi Owens‐Beek, Ana-Maria Bogdan, Xiaojing Lu, Meng Li, Shawn Ingram, Ryan McKay, Abigael Rice

Bibliographic record

VenueSustainability Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsAssembly of First NationsUniversity of Saskatchewan
FundersMinistry of Forests, Lands and Natural Resource Operations
KeywordsSubsistence agricultureGovernment (linguistics)Sustainable developmentEnvironmental resource managementPipeline (software)Environmental planningBusinessEconomyGeographyEconomicsPolitical scienceEngineeringArchaeologyAgriculture

Abstract

fetched live from OpenAlex

Abstract The Montney Play Trend (MPT) is a 1090 km2region in northeast British Columbia that produces approximately one-third of western Canada’s natural gas output. In response to a proposed expansion of the MPT in 2016, the Government of British Columbia launched a Regional Strategic Environmental Assessment (RSEA) to identify the necessary conditions to achieve sustainable environmental outcomes. In this paper, we describe the methods and scenario planning tools that were developed to estimate how the development of the MPT might affect the subsistence economies of First Nations in the region. To demonstrate the utility of our approach, two impact assessments—Prince Rupert gas transmission pipeline and the Coastal GasLink pipeline—are presented. While no scenario can provide a definitive portrayal of exactly what will happen in the future, the tools that were co-developed are serving as an effective starting point for exploring possibilities that are at least consistent with current knowledge and can serve as a platform for collaborative learning and conflict management.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.190
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.020
GPT teacher head0.267
Teacher spread0.246 · 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 designQualitative
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

Citations9
Published2021
Admission routes3
Has abstractyes

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