Rewriting the Social Contract: The Social Fund and Egypt's Politics of Retrenchment
Bibliographic record
Abstract
The politics surrounding retrenchment and social protection in the Middle East have been obscured by a broad ideological consensus that civil society has replaced the state as the site of social provisioning since the nineties. Contrary to the dominant “state retreat” narrative, the adoption of neo-liberalism in the region was not in fact uniformly accompanied by convergence around a minimal welfare regime. Why have processes of welfare retrenchment unfolded along contrasting patterns across the Middle East with some states explicitly redefining social policy frameworks, and others undermining access and effects of prevailing programs without dismantling them? The dissertation aims to contribute to our understanding of state-society relations in the region by closely examining recent welfare regime changes in Egypt. Why has Egypt pursued “hidden retrenchment” entailing dilution of universal benefits, conversion of social programs to new beneficiaries and institutional layering, without the explicit overhaul of welfare policy frameworks? What are the micro-level political influences shaping the retrenchment process on the ground? Using the Social Fund for Development as a window for understanding hidden retrenchment in Egypt, the dissertation demonstrates that external dynamics of globalization, and donor assistance do not mainly account for welfare regime restructuring. Similarly, the state’s fiscal status, and the underlying switch in development strategies cannot explain retrenchment patterns. Rather, I argue that the internationally dominant neoliberal development discourse has influenced some aspects of retrenchment reforms, and domestic political dynamics have molded hidden retrenchment in Egypt. The regime’s power maintenance logic and a prevailing moral economy of social entitlements explain the process. Micro-level qualitative and statistical analyses of retrenchment politics also reveal that intra-state agencies struggles, regime security concerns, the state’s tendency to fiscally penalize areas with a history of Muslim Brotherhood support, as well as the National Democratic Party’s patronage networks influence outcomes on the ground. My findings suggest that variations in retrenchment patterns across the region reflect important differences in states’ social bases of power, rather than external pressures or domestic economic dynamics.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.037 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".