The Politics of Protest Avoidance: Policy Windows, Labor Mobilization, and Pension Reform in France
Bibliographic record
Abstract
According to Paul Pierson and R. Kent Weaver, the "new politics of the welfare state" is about escaping the popular blame generated by cutbacks affecting a significant portion of the population. Although the concept of blame avoidance helps to explain the political logic of welfare state retrenchment, one can argue that a careful analysis of social policy reform should take into account a largely understudied phenomenon: protest avoidance. Especially present in countries with single party governments and politically active labor unions, protest avoidance is analytically distinct from blame avoidance because it occurs when policy-makers, facing direct and nearly inescapable blame, attempt to reduce the scope of social mobilization triggered by unpopular reforms. In recent decades, successive French governments have successfully introduced major--and unpopular--reforms in the field of pensions, despite the difficulties to frame blame avoidance strategies in the context of France's strong concentration of state power. Focusing on the 1993, 1995, and 2003 pension reform episodes, this paper seeks to demonstrate that right wing governments have generally tried to avoid protest rather than escape blame. We claim that the key element has been avoiding disruptive strike activities by the labor movement, which are highly political in France. We argue that right wing governments have attempted to divide the fragmented labor movement and overload the reform agenda while enacting its most controversial reforms during the summer holiday season. Protest avoidance thus represents a key political variable worthy of study in the literature on welfare state retrenchment. In the future, the concept of protest avoidance could be applied to other countries and policy areas in which elected officials attempt to impose unpopular reforms that trigger social mobilization.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".