Bibliographic record
Abstract
This research discusses the legal structures and policy interventions in Turkey related to the phenomenon of statelessness. In this context, individuals do not have citizenship and encounter serious obstacles in accessing fundamental rights and services. Situated at the intersection of Europe and Asia, Turkey receives enormous migration influxes, further complicating the issues of statelessness. The nation has enacted laws to recognize and protect stateless individuals, providing them with identity documents that grant access to essential services like health and work. However, systemic discrepancies, administrative tardiness, and low public knowledge impede the effective social integration and equal treatment of these individuals. The study contrasts 19 key Turkish legal texts with international law and academic commentary to determine how much Turkey's approach aligns with international norms. Although Turkey has ratified the 1954 Convention on Statelessness, it has yet to accede to the 1961 Convention, including its prevention provisions, specifically for children born to stateless individuals. This is putting large numbers of individuals, among them Syrian refugees, in a position of legal limbo. The study recommends that Turkey ratify the 1961 Convention, ease the procedures for ascertaining statelessness, enhance education campaigns on the rights of stateless persons, and develop comprehensive strategies for addressing the root causes. By embracing best practices from around the world and strengthening its legal framework, Turkey has the potential to become a leader in combating statelessness and ensuring equitable treatment for all individuals subject to its jurisdiction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".