Raport UNCHR – Tendințe globale: strămutarea forțată în 2018 (UNCHR, Geneva, 2019)
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 2018 Global Trends Report of UNHCR on forced displacement shows that there is a rise in the number of refugees as a result of persecution, conflict, violence, or human rights violations. By the end of the year 70,8 million individuals were forcefully displaced worldwide. The figure includes refugees and other displaced people not covered by UNHCR’s mandate and excludes other categories such as returnees and non-displaced stateless people. Sixty-seven per cent of refugees come from only five countries: Syria (6.7 million), Afghanistan (2.7 million), South Sudan (2.3 million), Myanmar (1.1 million), and Somalia (0.9 million). The report also focuses on the dire situation in Venezuela, which forced more than 3 million people to flee their country during 2018 due to lack of food and medicine, violence and poverty. The report also tackles relocation and integration of refugees. In 2018, 92,400 refugees were relocated in 25 countries, especially Canada, USA, Australia, UK and France. With regards to integration, it is difficult to distinguish between naturalized refugees and people who are not refugees. 62,600 refugees were naturalized, which is 10,800 less than in the previous year.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.058 | 0.001 |
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