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
Migration and international trade are two important dimensions of globalization. Migration plays an important role in development of countries. Immigrants send their remittances, ideas, innovation and investments to their home countries. Migrants can influence on countries’ trade, they are able to decrease the transactional costs for companies willing to trade. In this article has been tried to study the case of Iranian immigrants in Russia. We can see that Iranians have migrated mostly to developed countries such as USA, Europe, Australia, Canada and part of them have migrated to the Persian Gulf countries. And of course many of these immigrants have high levels of economic, human, social, and cultural potential, which can be used for social and economic development of the country. Iranians have migrated to two kinds of countries. First, those who are developed and second those with high income which have the potential of trade with Iran. When we look at these two groups they either migrated to American and European countries, which this group has a high educated and human capital background or they migrated to neighbor Persian Gulf countries that they have mostly strong economic backgrounds which increased the chance of trade. In this article Iranian businessmen have been interviewed and they have explained their roles in trade, and if they had any advantages in comparison with those in the home country.
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 | 0.002 | 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 it