The Role of Deliberative Mini-Publics in Improving the Deliberative Capacity of Multi-Stakeholder Initiatives
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
Multi-stakeholder initiatives (MSIs)—private governance mechanisms involving firms, civil society organizations, and other actors deliberating to set rules, such as standards or codes of conduct, with which firms comply voluntarily—have become important tools for governing global business activities and the social and environmental consequences of these activities. Yet, this growth is paralleled with concerns about MSIs’ deliberative capacity, including the limited inclusion of some marginalized stakeholders, bias toward corporate interests, and, ultimately, ineffectiveness in their role as regulators. In this article, we conceptualize MSIs as deliberative systems to open the black box of the different elements that make up the MSI polity and better understand how their deliberative capacity hinges on problems in different elements. On the basis of this conceptualization, we examine how deliberative mini-publics—forums in which a randomly selected group of individuals from a particular population engage in learning and facilitated deliberations about a topic—can improve the deliberative capacity of MSIs.
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 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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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