Bibliographic record
Abstract
Abstract This review article discusses MacLean’s study of the ideas of a group of economists and their embracing by an oligarchy of business groups to implement a Neoliberal agenda and its implications for American democracy. It mainly focuses on the Nobel Prize winning economist James McGill Buchanan and the industrialist Charles Koch. Business groups provided funds to Buchanan and others to train right-minded people in the precepts of Neoliberalism, established think tanks and institutes to disseminate their views, and ‘directed’ and/or provided advice and draft legislation for Republican politicians at both the state and federal level. Inspiration for how to achieve this Neoliberal ‘revolution’ can be found in Lenin’s 1902 What is to be Done?. The Neoliberal attack on government and statism is consistent with Orwell’s notion of doublethink. It constitutes a weakening of those parts of the state which are inimical to the interests of a wealthy oligarchy, the federal government and agencies/government departments who are viewed as imposing costs (taxes) on and interfering with (regulating) the actions of the oligarchy, and strengthening other parts such as state governments, the judiciary, at both the state (especially) and federal level and police forces to protect and advance their interests.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".