Temporary Protection for Ukrainians in the EU, UK, and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The full-scale Russian invasion of Ukraine, which started on 24 February 2022, led to the biggest armed conflict in Europe after WWII and forced more than 6 million Ukrainians to flee. This mass exodus induced the implementation of temporary protection policies worldwide, including the unprecedented activation of the Temporary Protection Directive by the Council of the European Union. Although occasionally applied, temporary protection is a relatively understudied concept, prompting the author to investigate its first-ever wide-scale application. The paper compares the temporary protection policies implemented for Ukrainians in the EU, UK, and Canada. The analysis includes descriptions of temporary protection policies in the chosen jurisdictions, their extensions, and the good and bad practices of their implementation. Since the Russo-Ukrainian War has become a protracted armed conflict, preventing most Ukrainians from a safe return, the paper also explores possible ways of their local integration in the EU, UK, and Canada. By comparing temporary protection policies in the mentioned jurisdictions, the author outlines the most preferred policy, making recommendations for policymakers on improving the delivery of current and future temporary protection policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it