“We Argued for a Long Time — Until the Tears of Stress…” (Scientific Controversy in the Community of Russian Logicians on the Pages of Public Press in the Early 20th Century)
Bibliographic record
Abstract
The paper discusses some aspects of logics development in Imperial Russia from the point of communication within the academic community. The author analyzes the tradition of writing critic books in response to the works of colleagues. The urgency of the research is determined by the fact that it is important to reveal traditions and patterns of the communication strategies within the academic community. The aim of the paper is to show the huge potential and value of polemic motivation to initiate publication activity of university scientists and academics. Numerous primary sources of the first quarter of the 20th century are used in the research. Many of them were not republished. The discussions that took place between debaters, colleagues or friends (A.I. Vvedensky – N.O. Lossky – S.I. Povarnin – I.I. Lapshin) and those who had personal grudge against their opponents (I.S. Prodan – A.I. Vvedensky), are reconstructed. A whole number of examples proving that Russian logicians in the early 20th century used monographs, handbooks, and papers as a platform for scientific disputes and exchange of opinions, including those with the international scientific community, are provided. The controversy in books was a kind of “distance” conference unfolded in time. Based on the results of the research, conclusions were made that the general situation with logics in the early 20th century is the time of extensive scientific discussions that often proceeded outside the classrooms. The academic community focused controversy in its diverse forms on various ideas generated by the most competent authors of that time. There was a specific canon for writing responses, i.e., following the opponent’s logic step by step, as well as revealing inaccurate citation, shift of emphasized thoughts, or even plagiarism. It seems important from the obtained results that, despite the tough style of retorts addressed to opponents, the strategies of opponency in monographs, handbooks, and papers provided technically for the search of some common foundations in subsequent research. The dispute of this type was an individual contribution to the accretion of knowledge and ranking of concepts. Books, as a reply, ensured a certain degree of responsibility in discussions; every word left its impression in the history of science. The results of the study are very important for researchers investigating social history of establishment of logics as a science, history of development of the Russian academic community, and strategies for holding scientific disputes.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".