Bibliographic record
Abstract
This article presents M. M. Bakhtin as a University professor through his own views of on the nature of university teaching: lecturing, seminars and colloquia, engaging students in debates and reflexive analysis of literary texts, “scientific thinking”, and working with bibliography. As a Chair of Russian and Foreign Literature department of the Mordovian National Pedagogical Institute (later the Mordovia State University), for a quarter of a century, Bakhtin was promoting teaching approaches that would support students’ informed, independent, analytical and reflexive learning. According to the minutes from different department meetings at his university, over the years, Bakhtin struggled to define and improve his own guidance and teaching in the Literature studies and the overall work of his department. His three pedagogical goals for a literary lecture were: 1) Communication of certain information on a given topic - establishing the level of students’ familiarity with the topic; 2) Fostering students’ scientific thinking; and 3) Fostering students’ aesthetic perception and taste. Some of his former students emphasized his erudition, pedagogic skill, and ability to stimulate his students’ imagination and reflective thinking.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".