Ancient crosses and tower-keeps : the politics of Christian minorities in the Middle East
Bibliographic record
Abstract
The interplay of religion and politics has been a consistent theme in the comparativepolitics of identity, and more specifically with regard to Middle Eastern politics Yetcoverage of religion and politics in the region is generally focused on the Muslimmajority and neglects the existence and impact of non-Muslim religious elements inMiddle Eastern societies. The most prominent of these are the various groups ofChristian Arabs.This work begins with a reassessment of common comparative theoretical approaches tothe study of religion and politics. It introduces a critical and dynamic constructivistapproach to religion, defining it as belief'. Using belief the political environment, andrelative demographics as a guide, it creates four general types of Christian groups as ameans to understand Christian group activation. These types match up with three generalmodes of engagement with the outside political culture in Middle Eastern contexts:competitive-nationalistic systems, neo-millet systems, and secular non-sectarian systems.These analytical tools are applied to the political activity of Christian groups in threeMiddle Eastern polities: Egypt, Lebanon, and Palestine. In Egypt, a stable neo-milletsystem is the result of the dominance of a single deferential organization amongChristians: the Coptic Orthodox Church. In Lebanon, years of competitive nationalisticpolitics have given way to an emergent neo-millet system as a result of the decline inidentity-based nationalistic parties and the increasing prominence of the traditionalChurch hierarchy. Among Palestinians, nominalism, deference, and voluntaristicactivism mix to create a neo-millet system with aspects of other systems of engagement.This study concludes that neo-millet systems are the natural outcome of a stronglyidentity-focused religious belief system among Arab Christians, one the author terms"tower-keep" theology. However, the dynamics of change fostered by new styles ofbelief, the challenges of responding to an eroding population base, and the influence ofdiaspora communities and coreligionists abroad all point to new systems of engagementto come in the future.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".