McCarthyism - phenomenon of American history. Contribution to history of Cold war
Bibliographic record
Abstract
Práce se si neklade za cíl detailně prozkoumat celý fenomén mccarthismu ve všech jeho aspektech, snaží se pouze postihnout okolnosti, které stály u jeho zrodu a poskytly mu vnitřní dynamiku, jež mu umožnily čtyřleté fungování. Vzhledem k charakteru práce i složité dostupnosti a množství pramenů se studie opírá o edici dokumentů z inkriminovaného období Alberta Frieda (McCarthyism, The Great American Red Scare, A Documentary History, New York - Oxford 1997), dále o edici pramenů sledující Trumanovo prezidentství sestavenou Williamem Hillmanem (The first publication from the personal diaries, private letters papers and revealing interviws of Harry S. Truman, New York 1952) a o paměti George Kennana (Memoirs 1950-196, Boston 1972). V neposlední řadě autor čerpal z dokumentů dostupných na internetu (A brief news and editorial history od judge Joe McCarthy, regular Republican candidate for the U.S. Senate; Kennanův "Dlouhý telegram"; řeč George C. Marshall na Harvardově univerzitě).
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".