Nationality and the Right to Enter:Assessing the Impact of Refusal of Entry for the Purpose of Statelessness Determination
Bibliographic record
Abstract
This article considers the legal situation of migrants, including rejected asylum seekers, who are unable to enter what was, until then, regarded as their country of nationality. This is because that country, without explicitly disputing their nationality, either prohibits their entry or de facto prevents them from entering its territory by failing to issue travel documents or respond to requests for consular assistance for organising return. By examining the conceptualisation of nationality in international law on the one hand, and the international legal definition of a stateless person on the other hand, the article argues that the right to enter the territory of one’s state is so essential to the concept of nationality that refusal of entry and denial of consular assistance for arranging return should be regarded as evidence that the state does not consider a person as its national. Based on this argument, the article further assesses the suitability of the United Nations High Commissioner for Refugees’ guidance on statelessness determination in cases of direct or indirect denial of entry. Ultimately, this contribution aims to clarify the scope of the international legal definition of a stateless person by strongly grounding its interpretation in the conceptualisation of nationality in international law.
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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 | 0.023 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".