Interviews with John Kenneth Galbraith
Bibliographic record
Abstract
For over half a century, Canadian-born John Kenneth Galbraith (b. 1908) has been among most visible of public intellectuals. His articulate and controversial best-selling books-including The Affluent Society, Economics and Public Purpose, and The New Industrial State-and his very partisan liberal Democrat political and public service activities secured a place for him among rich and famous of his time. He worked as an adviser to President John F. Kennedy, served as U.S. ambassador to India (1961-1963), and edited Fortune magazine during mid-1940s. Among American economists of any era, he is rivaled only by Thorstein Veblen for introduction of phrases that take on a life of their own in literate idiom. Such Galbraithian phrases as the conventional wisdom and society have become familiar even beyond Galbraith's remarkably wide readership. No other economist of twentieth century, excepting perhaps John Maynard Keynes, can claim so secure a place in belles-lettres of English-speaking world. This collection of interviews documents long career of an influential economist and political philosopher who has spent much of his professional life in public eye. Many of interviews are occasioned by publication of his books and contain their key themes such as importance of Keynes, need to include power in economic thinking, and neglected priorities of aesthetics, poverty, and environment in affluent America. The interviews also indicate Galbraith's wide-ranging public service and his frequent hobnobbing with political and intellectual elite. Through collection, which spans over four decades, Galbraith's erudition, wit, and impassioned liberalism shine through, making this volume an essential companion to his works. James Ronald Stanfield, a professor of economics at Colorado State University, is author of John Kenneth Galbraith, The Economic Thought of Karl Polanyi: Lives and Livelihood, and Economics, Power, and Culture: Essays in Development of Radical Institutionalism. Jacqueline Bloom Stanfield, a professor of sociology at University of Northern Colorado, is author of Married with Careers: Coping with Role Strain. Her work has appeared in such periodicals as Social Science Journal, American Journal of Economics and Sociology, and Review of Social Economy.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.013 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".