Secularization Theory’s Differentiation Problem: Revisiting the Historical Relationship between Differentiation and Religion
Bibliographic record
Abstract
Much theorizing about secularization tells a “differentiation story” that puts a historical process of structural differentiation at the center of its understanding of secularization. The heart of the story is the claim that the increasing differentiation of social spheres over time freed the “secular” spheres of life (politics, economics, etc.) from religious control or domination. This conceptual framing has been widely shared by scholars in the field, not only by adherents of the classical secularization paradigm, but also their leading critics in the supply-side and historicist–revisionist schools. While the story sometimes serves a purely descriptive function, at other times it is used to explain secularization (i.e., differentiation causes secularization). A close examination of the differentiation story, however, raises questions about the historical accuracy and theoretical plausibility of some of its core assumptions. Aspects of the differentiation story that require critical reconsideration include the empirical accuracy of its historical generalizations, its underspecified notion of “spheres,” and its explanatory assumption that some spheres are innately or properly nonreligious.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.046 |
| Scholarly communication | 0.004 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".