Bibliographic record
Abstract
This dissertation explores how Syrian refugees in the Netherlands navigate migration, integration, and belonging across gender and generations. Moving beyond policy or economic perspectives, it focuses on the emotional, relational, and identity dimensions of displacement and how refugees construct belonging and cope with exclusion in everyday life. Based on extensive ethnographic fieldwork and autoethnographic reflections, the study introduces the concept of the pendulum of belonging to describe Syrians’ oscillation between legal inclusion and cultural exclusion. It highlights how Syrians of different ages rebuild their lives and identities in distinct ways. Younger generations often find pathways through education and social mobility, while older refugees face structural barriers and the loss of professional roles, yet continue to cultivate resilience, family stability, and a dual sense of belonging to both the Netherlands and Syria. The dissertation draws on the Capability Approach, the Critical Life Course Perspective, and theories of Bordering, Othering, and Intersectionality to link structural constraints with personal agency. It contributes to forced migration research by illuminating gendered and generational dynamics and emphasizing the value of insider and reflexive research. Policy-wise, it calls for integration strategies that address intergenerational inequalities, emotional well-being, and the relational dimensions of belonging that refugees actively forge within Dutch society.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".