Cultural Differences in Children’s Recommended Punishment of Moral Transgressions
Bibliographic record
Abstract
Migration flows are as old as human history itself. In Greece, the first movements of people are recorded in the 13th century BCE and not stopped ever since. Inflows and outflows of people are a permanent future of Greek history. However, a distinction should be made between three types of flows. Firstly, people are forced to leave their country because of national agreements of resettlements. A world example of such resettlement was the exchange of population between Greece and Turkey in the first part of the 20th century. Secondly, people flee an area to save their lives because of war and prosecutions, including genocides. An example of such migration was the outflow of Greeks from Asia Minor because of the war between Turkey and Greece. Thirdly, people migrate for social reasons which may include economic, political and educational purposes. This was definitely the case of the post-Second World War period in Greece when many Greeks moved outside of Greece to find better jobs abroad (e.g., Germany); study abroad (e.g., U.K.); and to live in a democratic country (e.g., Canada, Sweden, etc.), because in Greece a dictatorship (1967-1974) had abolished democracy. Greece has also been on the receiving end of many migrants from all over the world for the same reasons. The latest example is the flow of Ukrainians who are coming to Greece due to the Russian-Belarus invasion of their country. These migration flows are examined in this paper. Keywords: migrants, refugees, migration policy, Greece, Ukraine
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".