Civil society initiatives for integrating refugees into Swedish society : Sustainable over time?
Bibliographic record
Abstract
This report analyses the progress of various initiatives initiated by civil society organisations in Sweden in 2015 to facilitate the integration of refugees.The report is part of a larger study funded by the Social Sciences and Humanities Research Council in Canada, which aims to compare the role of civil society in integration systems in Canada and Sweden.The study was conducted by Karla Escobar, who has a master's degree in political science, and Helene Ahl, a professor of business administration.We would like to express our gratitude to Marco Nilsson, an associate professor of political science, for his review and comments on the text.We would also like to thank Professor Benson Honig and his colleagues at McMaster University in Canada for their valuable cooperation.Furthermore, we extend our thanks to our reference group, which consists of representatives from the municipality and local associations.Their genuine interest in promoting sustainable integration activities has greatly influenced the focus of this study.We would also like to express our sincere appreciation to all the respondents who generously dedicated their time and commitment to this research.Lastly, we would like to acknowledge Sara Bref for her assistance in administration, and proofreading, and her valuable contribution in providing an excellent overview of the Swedish reception system.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".