Multiple Streams and Plausibility Cones: Using Concepts from Future Studies to Depict Policy Dynamics
Why this work is in the frame
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Bibliographic record
Abstract
Anticipating the future is a highly uncertain but essential task in policy-making made complex by the existence of both linear and non-linear policy dynamics. One framework which is useful in anticipating both kinds of change is the Multiple Streams Framework (MSF) which has expanded from looking mainly at aspects of policy-making such as agenda-setting to depicting other complex activities related to policy implementation and administration among others. Precisely how longer-term policy dynamics can be viewed through the MSF framework, however, remains unclear. This article re-examines common depictions of policy trajectories and argues that using a concept borrowed from Future Studies - the “plausibility cone” – can fill this gap in MSF modelling and help both policy-makers and policy scholars better understand likely and unlikely possible policy futures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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