Immigrant organisations in Slovenia
Bibliographic record
Abstract
The paper provides a comprehensive inventory and presentation of the activities of immigrant organizations in Slovenia. The organization and activities of immigrants in associations or other organizations are an important form of their civic participation in the country of immigration. In 2023, 134 immigrant organizations were operating in Slovenia, most of which are associations. This paper focuses mainly on analysing their activities, the time of their establishment, their ethnic organization and the geographical distribution of these organizations. The analysis shows that the mono-ethnic organization of immigrant communities is prevalent in Slovenia. The vast majority of these organizations were founded by members of the communities from the former Yugoslavia, who are the most numerous immigrants and have the longest presence in Slovenia. As a result, their organizations are among the oldest of all immigrant organizations, operate over a wider geographical area and show a greater diversity of activities than those of other immigrant groups. Most immigrant organizations operate in urban areas, which are also home to the highest number of immigrant populations. Almost all immigrant organizations in Slovenia are involved in cultural activities, mainly preserving the original cultures and languages of immigrants. A good quarter of them are also involved in various educational activities, and their activities in the fields of advocacy, humanitarianism and sport are also worth mentioning.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".