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Record W2047474340 · doi:10.1080/13668790902753070

‘You’re In Oil Country’: Moral Tales of Citizen Action against Petroleum Development in Alberta, Canada

2009· article· en· W2047474340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEthics Place & Environment · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of AlbertaMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitizenshipAction (physics)Collective actionPetroleum industryPoliticsEnvironmental ethicsPetroleumPolitical scienceSpace (punctuation)SociologyLawEngineering

Abstract

fetched live from OpenAlex

The Canadian province of Alberta has experienced phenomenal growth in its oil and gas industry. As the petroleum–industrial complex expands it has sparked a number of community-based conflicts over noxious facilities that are seen by some to be the cause of a number of health problems. The research reported here used two case studies to examine siting conflicts involving natural gas extraction facilities in rural Alberta. We found that the stories shared by citizens involved in these conflicts functioned as ‘moral tales’. These moral tales were political in the way they challenged implicit and institutionalized rationales for redistributing benefits and burdens of oil and gas development. They also created a space for collective action by articulating spatial transgressions and by constructing a type of moral citizenship.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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