Policy Design and Non-Design: Towards a Spectrum of Policy Formulation Types
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
Public policies are the result of efforts made by governments to alter aspects of behaviour—both that of their own agents and of society at large—in order to carry out some end or purpose. They are comprised of arrangements of policy goals and policy means matched through some decision-making process. These policy-making efforts can be more, or less, systematic in attempting to match ends and means in a logical fashion or can result from much less systematic processes. “Policy design” implies a knowledge-based process in which the choice of means or mechanisms through which policy goals are given effect follows a logical process of inference from known or learned relationships between means and outcomes. This includes both design in which means are selected in accordance with experience and knowledge and that in which principles and relationships are incorrectly or only partially articulated or understood. Policy decisions can be careful and deliberate in attempting to best resolve a problem or can be highly contingent and driven by situational logics. Decisions stemming from bargaining or opportunism can also be distinguished from those which result from careful analysis and assessment. This article considers both modes and formulates a spectrum of policy formulation types between “design” and “non-design” which helps clarify the nature of each type and the likelihood of each unfolding.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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