Bibliographic record
Abstract
Nicknames and pseudonyms are one of the subjects that should be studied carefully in Turkish literature. Nicknames and pseudonyms are “fake names” and “symbols” that poets and writers use to hide their real identities for various reasons. These names and symbols, which are extremely important in identifying the works of poets and writers, allow literary historians to make more accurate analyzes about poets and writers. Therefore, each new nicknames and pseudonym identified has a great importance in eliminating the deficiencies of the literary history. Ahmet Rasim (1865-21 September 1932) produced works in different literary genres such as poetry, stories, novels, memoirs, anecdotes, conversations, articles, essays, translations, history, criticism, and monographs throughout his 48-year writing life. The author also has school books and scientific works. However, his main qualification is journalism. Ahmet Rasim, who makes a living with his pen, wrote and published articles in different literary genres under different pseudonyms in the magazines and newspapers he worked for. Situations and thoughts like not being confident enough to put your real name on your works when he was just starting his life in literature and the press, show the writer staff of magazines and newspapers rich, distinguish between humorous and serious writing, attracting female readers attention, avoiding the reaction of his works depending on the social, political and literary conditions of the period and breaking of the censor can be counted among the reasons why Ahmet Rasim used different nicknames and pseudonyms. Although Ahmet Rasim uses many nickname and pseudonyms, very few of them are known by the literary world. In this study, the nickname and pseudonyms that we determined to be used by the author will be revealed. Keywords: Ahmet Rasim, literature and press, journalism, nickname and pseudonyms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 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".