Labour market integration of refugees in Sweden – Analysing the interactions of CSOs at different levels
Bibliographic record
Abstract
There has been a gap in knowledge regarding how civil society organisations (CSOs) interact at different levels when working to integrate refugees into the labour market—its causes and limitations. To contribute to filling the gap, this study employs both a rational choice perspective and sociological institutionalism to analyse how and why CSOs in Jönköping municipality in Sweden interacted with other relevant actors, both other CSOs (horizontally) and the public sector (vertically), to integrate refugees into the labour market after the refugee crisis in 2015 and what challenges they faced. It analyses different forms of interaction, that is, not only the relationship between the state and the civil society but also the one between different civil society organisations, which brings a new analytical dimension to the concept of coproduction to support refugees. By analysing the organisations’ interactions at different levels, the study identifies four themes: Striving to be flexible and service-minded organisations; between rational choice and institutionalisation of horizontal interactions; obstacles to horizontal interactions; and difficulty of measuring goal attainment.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".