Bibliographic record
Abstract
Jacob Viner, the economic theorist and historian of economic thought, was born and raised in Montreal, the son of immigrant parents from eastern Europe. As an undergraduate he attended McGill University, where he was taught economics by Stephen Leacock, the famous humorist. Leacock used texts by Mill and Walker, Milk and Water, as the students referred to them, showing ‘good judgment’ according to an account that Viner gave later in life. For graduate work he went to Harvard, where he earned a Ph.D. in 1922. He was a student and eventually became a close friend of Frank W. Taussig, the well-known authority on economic theory and international economics. At that time and during the earlier part of Viner’s career he and Taussig were rare specimens in what was, except for a very few others, essentially a ‘wasp’ establishment. But in other respects their background was quite different. Viner was a self-made man who had emancipated himself from the immigrant quarter of Montreal, while Taussig was born into a patrician family with wealth and native culture.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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".