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"Dirty Oil, Ethical Oil: Categorical Illegitimacy and the Struggle over the Alberta Oil Sands"

2013· article· en· W1980064677 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAcademy of Management Proceedings · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLegitimationLegitimacyCONTESTCategorical variableDialecticSemioticsConstruct (python library)Field (mathematics)SociologyEpistemologyUnpackingSocial psychologyPolitical sciencePsychologyLawComputer science

Abstract

fetched live from OpenAlex

Organizational research has focussed almost exclusively on the role of legitimate categories of practices, strategies, and structures in organizational phenomena, while neglecting the creation and use of illegitimate categories. To address this gap, we draw on social theories of legitimacy and social semiotics to show how illegitimate cultural categorizations are dialectical, embedded within symbolic systems, and how they are used to shape organizational action. More specifically, we analyse the processes by which various participants construct categorical illegitimacy in ongoing public debate about a controversial energy source – oil from Alberta’s oil sands. These influential actors employ images and words to contest opponent organizations taking a discursive stake in this field as they struggle over the legitimacy of extracting this form of oil. Based on our study, we offer a model for understanding the visual and emotional processes of categorical legitimation and delegitimation

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.224
Teacher spread0.213 · 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