"Dirty Oil, Ethical Oil: Categorical Illegitimacy and the Struggle over the Alberta Oil Sands"
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.
Bibliographic record
Abstract
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
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it