Multistakeholder Collaboration as Symbolic Marketplace and Pedagogic Practice
Bibliographic record
Abstract
This article focuses on the role of power in multistakeholder collaboration. It considers this form of organization from a nontraditional, Bourdieun perspective, which has the authors focus on the how of power and on the role of language in the constitution and the exclusion of voice. A case study—a collaboration convened by a scientific task force to resolve an environmental conflict in Canada’s Banff National Park—is introduced, and this is read off against a number of Bourdieu’s concepts, namely capital, field, habitus, and misrecognition, doxa, and symbolic violence. Through such a reading, the article offers insights into elements of both surface and deep-structure power. The article, by focusing on a science-driven, environmental multi-stakeholder collaboration, also challenges common-sense constructions of the environment and raises concerns over the presumed neutrality or nonpolitical nature of both scientific and economic discourse.
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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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.050 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".