Teknik Dinlemeye Dair! "Gizli Dinleme Kanunlarõna ve Uygulamalarõna Dair Bir Aratõrma"
Bibliographic record
Abstract
ABSTRACT IN ENGLISH: This book has two parts. The first part covers the historical evolution of the American wiretapping legislation, summary of the American Wiretapping Criminal Procedure, the summary of Communication Assistance for Law Enforcement Act of 1994 (CALEA), and the privacy and property right problems in the CALEA and the corresponding suggestions. The second part of the book covers analytical summary and comparative analyses of legal positions of wiretapping in Britain, Canada, Germany, France, Israel, and Turkey. (Note that the manuscript is currently in Turkish. For the English version of the manuscript, please contact to author. ABSTRACT IN TURKISH: Kitap iki bolumden olusmaktadir. Ilk bolumde, Amerikan teknik dinleme mevzuatinin hukuki gelisimi, Amerikan Teknik dinleme ceza usulunun ozeti, Iletisim Sirketlerinin Kolluk Kuvvetlerine Yardimi Kanununun (CALEA) ozetini, CALEA ile ilgili mulkiyet ve ozel hayatina iliskin sorunlar ve cozuum onerileri bulunmaktadir. Ikinci bolumde Ingiliz, Kanada, Alman, Fransiz, Israil ve Turk hukuk sistemlerinde, teknik dinlemenin anayasal ve ceza usul hukuku acisindan yeri, analitik olarak ozetlenmekte ve mukayeseli analizi yapilmaktadir.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 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".