You can call me a comparativist, I studied American and Russian mass consciousness” / Interview prepared by B.Z. Doktorov
Bibliographic record
Abstract
The author describes his 50 years of experience in studying public opinion in America, the Soviet Union and Russia. This includes research at the Institute of American and Canadian Studies of American mass consciousness, the study of Americans’ attitudes towards economic and social problems, Soviet-American relations; and collaboration with leading American public opinion polling centers — the Gallup Institute, the University of Michigan, National Opinion Research Center in Chicago, studying the work of the L. Harris and M. Field polling services, the CBS-New York Times, ABC-Washington Post centers, the polling organizations of the Democratic and Republican parties, presidential advisors on public opinion. The author implemented his American experience in organizing the study of public opinion in the USSR and then in Russia when creating the Russian Public Opinion Research Center (VCIOM), the Center for Studying Public Opinion of the Presidential Administration of Boris Yeltsin, the Agency for Regional Political Research, and other survey centers. Analyzed is the use of sociological surveys in Boris Yeltsin’s presidential election campaign in 1996. The author has conducted several joint Soviet/Russian-American public opinion studies: “Television and society”, “Soviet and American children on the threat of war”, “National problems of Russia”. The author describes his experience in communicating with leading American and Russian experts in the study of public opinion — G. Gallup, L. Harris, Yu.A. Zamoshkin, B.A. Grushin.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".