Cumhuriyet döneminde Heybeliada (1923’ten günümüze)
Bibliographic record
Abstract
Çalışmamızda Cumhuriyet döneminde Heybeliada tarihi ele alınmıştır. Cumhuriyetin kuruluşundan itibaren Heybeliada ile ilgili kaynaklar incelenmiş ve bu kaynaklara göre adanın tarihi çıkarılmıştır. Adanın siyasi, sosyal, kültürel tarihi hem birincil hem de ikincil kaynaklar incelenerek yazılmıştır.\n\tAda’da azınlıkların veya Türklerin nüfus yoğunluğu siyasi durumların belirlenmesinde etkin bir rol oynamıştır. Yine aynı şekilde nüfusun kültürel alanı ve kurumları da nasıl etkilediği gözler önüne serilmiştir. Heybeliada Sanatoryumu ile birlikte adanın günümüzdeki sağlık koşulları verilmiştir. Bunlardan başka spora ve adaya gelip giden, yaşayan önemli şahsiyetlere değinilmiştir. \n\n\nABSTRACT\n\tOur study deals with the history of the Heybeliada in the republic period. Sources that related to the Heybeliada-even the sources that belong to the early republican era- was examined, and according to these sources the island’s history is written. Island’s political, social and cultural history was written by examining both primary and secondary sources.\n\tBoth minorites and the Turks population played an important role to determine their political situation. Also, the effects of the population to the cultural field and the institutions was also examined in this study. Along with the Heybeliada Sanatorium the medical condition of the island was also studied in this work. Also, sport activities within the island and the famous people that visited or stayed the island was examined.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".