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Record W2793981208 · doi:10.1525/cse.2017.000877

Public Trust in Environmental Decision-Making: A Case Study of Shale Gas Regulation in Kent County, New Brunswick

2018· article· en· W2793981208 on OpenAlexaffabout
Stewart Fast, Laura Nourallah

Bibliographic record

VenueCase Studies in the Environment · 2018
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSkepticismShale gasIndigenousRepresentation (politics)Public involvementOil shalePublic participationPublic trustEnvironmental planningPolitical sciencePublic administrationGeographyLawEngineeringPublic relationsPolitics

Abstract

fetched live from OpenAlex

The existence of trust and confidence in public authorities and in the rules and the outcomes of environmental and other regulatory assessment processes is highly important. This case examines a region that was overwhelmingly distrustful of public authorities making decisions about shale gas development. Kent County is a rural area in New Brunswick, Canada, featuring coastal and inland villages and a unique mix of three cultures (Mi’kmaq, Acadian, and Anglophone). Through a combination of interviews (n=20) and a survey (n=500), we identified three main reasons for the lack of confidence: (1) skepticism over capacity; (2) scandals and controversies; and (3) challenges of aligning with indigenous epistemologies and questions of representation.

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)0.004
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0240.008
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.261
Teacher spread0.224 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

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