Compassionate Neoliberalism?: Evangelical Christianity, the Welfare State, and the Politics of the Right
Bibliographic record
Abstract
Faith, Government, and Neoliberalism The study of neoliberalism has been a popular theme in political science, geography, and sociology for the past decade. The focus of this vast literature varies considerably, but has been generally aimed at understanding the ways in which the ideas of midtwentieth century neoliberal ideologues like Friedman, Hayek, and von Mises have been morphed into the actualized policy apparatus at various scales in different countries.1 Research projects under this rubric have sought to explore different dimensions of this process, from the institutions that promote such ideas, like bond-rating agencies, think tanks, and the IMF, to the political logics underlying it.2 One common focus of these studies is the decentralizing or dismantling of Keynesian welfare and its replacement with policies that emphasize markets, individual responsibility, and a diminished governmental safety net—all of which are key principles of idealized neoliberalism.3 Nongovernmental organizations (NGOs) of all sorts have been called upon in this environment to absorb some of the responsibilities once ensconced in the Keynesian state. Though most religious NGOs (also referred to in this paper as “faith-based organizations” (FBOs)) have a complicated set of objectives and processes that predate the rise of neoliberalism, many have been integrated into an effort to reduce reliance on traditional, Keynesian forms of delivery in the United States and elsewhere. Such organizations are increasingly called on to deliver Keynesian services that were rolled-back through cuts.4
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| 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".