Bibliographic record
Abstract
Readers and students of Ayn Rand will value seeing in this collection of interviews how Ayn Rand applied her philosophy and moral principles to the issues of the day.Objectively Speakingincludes half a century of print and broadcast interviews drawn from the Ayn Rand Archives. The thirty-two interviews in this collection, edited by Marlene Podritske and Peter Schwartz, include print interviews from the 1930s and edited transcripts of radio and television interviews from the 1940s through 1981. Selections are included from a remarkable series of radio broadcasts over a four-year period (1962-1966) on Columbia University's station WKCR in New York City and syndicated throughout the United States and Canada. Ayn Rand's unusual and strikingly original insights on a vast range of topics are captured by prominent interviewers in the history of American television broadcasting, such as Johnny Carson, Edwin Newman, Mike Wallace, and Louis Rukeyser. The collection concludes with an interview of Dr. Leonard Peikoff on his radio program in 1999, recalling his 30-year personal and professional association with Ayn Rand and discussing her unique intellectual and literary achievements. Ayn Rand is the best-selling author ofAtlas Shrugged,The Fountainhead,Anthem, andWe the Living. Fifty years or more after publication, sales of these novels continue to increase.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.109 | 0.043 |
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".