A Question of Authenticity: Status Quo Bias and the International Energy Agency's World Energy Outlook
Bibliographic record
Abstract
Over the past decade, transition scholars have argued that images of the future (of what sort of change is possible or probable, desirable or undesirable) play a critical role in societal transitions, and there is a long-standing tradition of analysis that points out the political significance of visions of the future. This article explores the politics of the future in sustainability transitions by looking at controversy surrounding a prominent global energy future report—the International Energy Agency's World Energy Outlook—between 1998 and 2008/2009. A key theme of this controversy was that the Outlook's record on global oil supply projections demonstrated a bias towards the preservation of the status quo. Based on research interviews conducted with key participants in this controversy, and a review of Outlooks produced between 1998 and 2008, we explore the main ‘sites of contention’ in the allegation of bias from both an ‘internal’ (sympathetic) and an ‘external’ (critical) perspective. We argue that the politics of bias have less to do with one's relationship vis-à-vis the preservation of the regime, and more to do with a question concerning the speaker's authenticity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.053 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".