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Record W2026186204 · doi:10.1177/1748048510386745

Picturing environmental risk: The Canadian oil sands and the National Geographic

2011· article· en· W2026186204 on OpenAlexaffabout
Chaseten Remillard

Bibliographic record

VenueInternational Communication Gazette · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Calgary
FundersNational Geographic Society
KeywordsResource (disambiguation)Environmental communicationSublimeOil sandsVisual communicationRisk communicationPublic opinionEnvironmental resource managementEnvironmental planningPublic relationsSociologyPolitical scienceGeographyBusinessAestheticsAdvertisingEnvironmental scienceComputer scienceRisk analysis (engineering)ArchaeologyLawArt

Abstract

fetched live from OpenAlex

The National Geographic Magazine photographic essay on the Canadian oil sands presents an excellent case study of how environmental risk is communicated visually. The images express an inherent tension between nature-as-sublime and nature-as-resource, and mobilize various discourses related to environmental degradation and resource management. Through a specifically visual approach to the communication of risk, this article provides theoretical insight into how risk is perceived differently within various social contexts and concludes that the visual communication of risk may not substantially raise levels of public engagement and initiative.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.042
Threshold uncertainty score0.308

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0180.015
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.282
GPT teacher head0.368
Teacher spread0.086 · 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

Citations50
Published2011
Admission routes2
Has abstractyes

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