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Record W2907972515 · doi:10.29173/cjs29415

Big Oil U: Canadian Media Coverage of Corporate Obstructionism and Institutional Corruption at the University of Calgary

2018· article· en· W2907972515 on OpenAlexaffvenueabout
Kevin McCartney, Garry Gray

Bibliographic record

VenueThe Canadian Journal of Sociology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsCorporationMandateLegitimacyPublic broadcastingFrame analysisLanguage changePolitical sciencePublic relationsCorporate governanceSociologyCorporate social responsibilityContent analysisPublic administrationSocial scienceManagementLawEconomics

Abstract

fetched live from OpenAlex

A 2015 investigation by the Canadian Broadcasting Corporation (CBC) into the involvement of Enbridge Inc. at the University of Calgary drew widespread media attention in Canada on issues of academic integrity and legitimacy as well as renewed attention to the increasing centrality of corporate dollars in public institutions. All of this was further embedded in a public consideration of climate change and the contested legitimacy of carbon corporate interests. A qualitative content media analysis of 70 published stories from Canadian news sources reveals a stark contrast between corporate and non-corporate media frames. Our analysis shows the parallel efforts of the University of Calgary, Enbridge, and corporate media to frame out the central issues of corporate obstructionism in public institutions and, equally, institutional corruption around the mandate, purpose, and intention of those public institutions.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.015
Science and technology studies0.0120.005
Scholarly communication0.0080.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.067
GPT teacher head0.266
Teacher spread0.199 · 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.

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 routes3
Has abstractyes

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