Bibliographic record
Abstract
Elections in advanced industrialized democracies – like the United States, Canada, and Western Europe – serve to aggregate citizens’ interests and preferences. They determine which elites and political parties control institutions that wield influence over society, and how that political power can be reordered over time. Elections also occur in many authoritarian systems, though irregularities and fraud often mar them. Moreover, they do not necessarily reorder political power – indeed, autocrats’ right-hand men often retain ironclad control over key institutions (e.g., military, police) regardless of electoral outcomes. In light of this reality, this chapter asks what the purposes of elections are in authoritarian regimes if they do not help to genuinely signal citizens’ preferences or redistribute power. This chapter addresses this topic, focusing on the different functions of elections within the authoritarian regimes of the Middle East and North Africa (MENA). The MENA region differs from other world regions insomuch as it exhibits only solidly authoritarian regimes or transitional democracies trending toward authoritarianism, like Turkey and Sudan. In particular, the chapter illustrates how authoritarian elections are utilized for three major functions: to help release or assuage political pressure, to distribute clientelist resources, and to cultivate political symbolism. All these functions, this chapter argues, serve to buttress autocrats’ power and reinforce their regimes. The chapter, then, toggles down to examine how these three different functions manifest in elections occurring at the executive (i.e., presidential or prime ministerial levels), legislative (i.e., parliamentary level), and local (i.e., municipal) levels of political power. Examples from across the Middle East, especially from Morocco, Syria, Yemen, Egypt, Jordan, Algeria, Turkey, and others, are used to show how elections carry out these three different functions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".