Neoliberalism and IQ: Naturalizing economic and racial inequality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How did IQ become an important means of naturalizing economic and racial inequality and supporting neoliberal visions of a fully privatized, free market society? I show how post-WWII neoliberals and libertarians could employ ideas of “innate intelligence” to promote the reduction of government funding of social programs. For extreme libertarian economist Murray Rothbard, inequality among individuals and ethnicities was self-evident from human history and the a priori examination of the “natural order,” but IQ data could also be employed in the fight against “egalitarianism.” Any attempt to interfere in this “natural order,” such as civil rights legislation, was viewed as inherently evil. For libertarian Charles Murray and more mainstream neoliberals such as Milton Friedman, empirical research on intelligence was an effective means of influencing public perception and policy on welfare, affirmative action, and immigration. I discuss recent work on “national intelligence” in relation to neoliberal projects and enduring fears regarding reproduction and family.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it