Bibliographic record
Abstract
Consultation may have the potential to be an effective mechanism of collaborative governance but only insofar as it is empowered. Empowerment in this context means that consultations are characterized by a degree of decision-making power or, at least, the power to directly influence decisions. This potential for empowered consultation is far from realized in policy processes. Not only is it a long road to consultations that go beyond merely justifying elites’ decisions, but there is even further to go toward entrenching empowered consultation in the formulation and implementation of public policy. In this paper, we identify categories of consultation, including their features and their ends, ranging from the disempowered to the empowered. We also make a normative argument for empowered consultation, while articulating the limitations of this mechanism.
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.
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 | 0.062 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.053 |
| Scholarly communication | 0.026 | 0.042 |
| Open science | 0.004 | 0.029 |
| Research integrity | 0.018 | 0.014 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".