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Record W6930703871 · doi:10.5281/zenodo.13886351

Immigrant organisations in Slovenia

2024· article· en· W6930703871 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldPsychology
TopicEmotion and Mood Recognition
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationEthnic groupDiversity (politics)Quarter (Canadian coin)Distribution (mathematics)Social organization

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0770.055

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.

Opus teacher head0.046
GPT teacher head0.296
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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