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Record W2986412471 · doi:10.1504/ijram.2019.103339

Risk communication and public engagement in CCS projects: the foundations of public acceptability

2019· article· en· W2986412471 on OpenAlexafffund
William Leiss, Patricia Larkin

Bibliographic record

VenueInternational Journal of Risk Assessment and Management · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Ottawa
FundersQueen's UniversityMcGill UniversityCarbon Management CanadaUniversity of Ottawa
KeywordsTransparency (behavior)Public engagementPublic relationsPerceptionBusinessPublic participationRisk perceptionEnvironmental resource managementRisk analysis (engineering)Political scienceEnvironmental economicsPsychologyEconomics

Abstract

fetched live from OpenAlex

This paper posits that an important goal of public engagement for carbon capture and storage (CCS) projects as being public and social acceptance for those projects. It argues that acceptability is the end of a long, logical chain of social interactions, which ideally starts with: 1) the public perception of the risks and benefits associated with CCS; moves through 2) effective communication of risks and benefits by project proponents; 3) involves robust and credible measures for public engagement; 4) results in authoritative decision processes that transparently reflect the results of engagement. Each of these components of acceptability is described with respect to both actual experience with CCS projects to date and the relevant literature. Conclusions point to the special importance of full transparency and public understanding of credible risk assessments for these projects.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.371
Teacher spread0.331 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations30
Published2019
Admission routes2
Has abstractyes

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