Our man at the top: How the Seven Mountains Mandate and Paul Weyrich’s Last Testament have shaped the presidency of Donald Trump
Bibliographic record
Abstract
Through a comparative analysis, this article reveals the striking similarities between the Seven Mountains Mandate – a dominionist evangelical ideology – and the strategy to ‘restore the republic’ described in Paul M. Weyrich and William S. Lind’s 2009 book The Next Conservatism , also called Paul Weyrich’s Last Testament. The article highlights three points of convergence: (1) strategically, both employ a top-down approach to gain political power with the goal of replacing the existing political ‘elite’ and bolstering fundamental cultural changes; (2) structurally, their proponents operate within networks of seemingly independent yet interdependent organizations and groups; and (3) ideologically, both represent conservative versions of Christian nationalism. Furthermore, the article shows how the strategies’ theoretical underpinnings have manifested in a strong and enduring endorsement of Donald Trump, not only facilitating his election and re-election, but also contributing substantially to shaping his political agenda.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".