Creative laboratory of the author: functional bilingualism in the preparation of a written text
Bibliographic record
Abstract
The report examines the peculiarities of bilingualism of the outstanding Russian-American sociologist Pitirim Sorokin (1898–1968) based on his archival working materials from the University of Saskatchewan (Canada). The purpose of the study is to identify and explain the linguistic features of his scientific thinking in connection with the conditions of translinguism. Based on the material of Pitirim Sorokin’s working notes, the features of his work on the creation of the book “Contemporary Sociological Theories” (1928) are considered. Correspondences between the preparatory notes and the final text of the book are established. The specifics of translingual practices in the scientific activity of a scientist are revealed. Archival manuscripts and notes allow you to trace not only the process of changing the language and switching codes. The use of a mixed meta-language by Pitirim Sorokin in the work on the preparatory materials of the book has been established. At the same time, a functional distribution of language codes is revealed. Russian language is a working tool of scientific thinking, planning and management of research activities.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".