The guise of the gentleman scholar: Criticism and conduct around J. Philippe Rushton’s general factor of personality
Bibliographic record
Abstract
I examine the reception of British-Canadian psychologist and race scientist J. Philippe Rushton’s late-career project: the general factor of personality (GFP). Proposed as a domain of personality at the apex of all other psychometric personality factors, Rushton argued that the GFP was an evolutionarily important feature of human development. Unlike Rushton’s research and public communications on race, sexuality, and intelligence, his GFP research did not receive the same ethical derision. Building on recent approaches to understanding the processes and persistence of psychological race science, I argue that Rushton’s GFP was largely critically assessed on its internal merits (like methodology) rather than on external ones considering social context. With recent work on the legacy keeping of intelligence researcher Arthur Jensen in mind, I explore the image and conduct of the gentleman scholar both as a way that Rushton is remembered and in relation to how certain types of criticism can allegedly be precluded from consideration. I conclude that limiting our criticism to the traditional boundaries of gentlemanly conduct is insufficient when scrutinizing psychological research, and that the wider context of Rushton’s bad science (badly constructed and bad for society) ought to have been a part of the GFP’s reception.
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 | 0.023 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.053 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.001 | 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".