LATINISMS IN NAMES OF INSTITUTIONS, MOTTOES AND RELIGIOUS ENGLISH TEXTS IN THE CONTEXT OF THE HISTORY OF ENGLISH LANGUAGE
Bibliographic record
Abstract
The article offers a thorough examination of the functioning of Latin elements in the names of institutions, mottos, and symbols of Englishspeaking countries within the framework of the studying of the history of the English language.Although Latin has lost its status as a spoken language, it continues to exist in the modern cultural space, serving as a bearer of symbolic meanings, a marker of prestige and authority, and a bridge between the ancient and the contemporary worlds.The authors trace the historical origins of the spread of Latin in the United Kingdom, the United States, Canada, and other Englishspeaking countries, and examine its influence on the formation of political, legal, and educational traditions.Particular attention is paid to Latin mottos as elements of heraldry and institutional identity that reflect core valuesfaith, knowledge, honour, and serviceand have the capacity to consolidate communities around shared ideals.Based on a semantic analysis, the study offers a thematic classification of mottos and identifies their role in preserving and transmitting
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".