When Policies Undo Themselves: Self‐Undermining Feedback as a Source of Policy Change
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
Most studies of policy feedback have focused on processes of self‐reinforcement through which programs bolster their own bases of political support and endure or expand over time. This article develops a theoretical framework for identifying feedback mechanisms through which policies can become self‐undermining over time, increasing the likelihood of a major change in policy orientation. We conceptualize and illustrate three types of self‐undermining feedback mechanisms that we expect to operate in democratic politics: the emergence of unanticipated losses for mobilized social interests, interactions between strategic elites and loss‐averse voters, and expansions of the menu of policy alternatives. We also advance hypotheses about the conditions under which each mechanism is likeliest to unfold. In illuminating endogenous sources of policy change, the analysis builds on efforts by both historically oriented and rationalist scholars to understand how institutions change and seeks to expand political scientists’ theoretical toolkit for explaining policy development over time.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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