Narrowing the Climate Field: The Symbolic Power of Authors in the IPCC's Assessment of Mitigation
Bibliographic record
Abstract
Abstract This article provides a critical analysis of the Intergovernmental Panel on Climate Change (IPCC) as a boundary organization using Bourdieu's concepts of field, habitus, and symbolic power. The article combines quantitative, network, and survey data to explore the authorship of Working Group III's contribution to the IPCC Fifth Assessment Report (AR5). These data reveal the dominance of a small group of authors and institutions in the production of knowledge that is represented in the AR5 report, and illuminates how the IPCC's centrality to the field of climate politics is shaping the research and publication strategies of researchers within that field. As a result, the study is able to identify organizational avenues for deepening the involvement and symbolic power of authors from the global South in IPCC assessments of climate change. While empirically, the results of this study lead us to question the IPCC as an assessor of knowledge, theoretically, it suggests that particularly in the international sphere, the use of the boundary organization concept risks overlooking powerful networks of scientific actors and institutions and their broader implication in the politicization of science.
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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 | 0.031 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".