Bibliographic record
Abstract
Like its predecessor, The Dynasty of Chernigov 1054–1146 , this book is based on an examination of primary sources. From among these, the chronicles of Rus′ have once again served as the main reservoir of information. Nevertheless, they cannot be taken at face value. We must keep in mind that not one chronicle copy from the twelfth or the thirteenth century has survived. Chronicles written at the courts of the princes under investigation were incorporated into later compilations and have come down to us, for the most part, in those from the fifteenth and the sixteenth centuries. Consequently, in evaluating chronicle accounts, we must keep in mind the biases of the original chronicler and of later compilers. Moreover, errors crept into the texts during the course of recopying when scribes inadvertently made mistakes through ignorance, carelessness, or fatigue. In some instances compilers changed the text when they sought to improve the original in the light of their own world-view. The dating also produces special difficulties. The chroniclers use two systems of dating: the March ( martovskiy ) Year and the Ultra-March ( ul′tramartovskiy ) Year. Both years begin with March. When the chronicle uses the March Year, the correct January year of the Christian or Common Era is obtained by taking the chronicle date, for example 6732, the date from the creation of the world according to the Byzantine calendar, and subtracting 5508, the year before Christ in which, according to Byzantine reckoning, the world was created. This gives us the January year 1224 ce .
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.357 | 0.200 |
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".